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This report presents the findings of a detailed household survey undertaken in Lelaitich location of Sigor division, Bomet district, during December 1997. The survey covered 225 households in three sub-locations, namely, Lelaitich, Kapsabul and Lugumek. The main objective of the baseline survey was to collect information from households so as to give insights into the socioeconomic profile of the population, and identify causes of poverty and the coping mechanisms adopted by households and the community. The research was funded by ACTIONAID-Kenya.
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ACTIONAID-KENYA
REPORT OF THE HOUSEHOLD SURVEY OF LELAITICH LOCATION, BOMET DISTRICT
by
John Thinguri Mukui
Prepared for ACTIONAID-KENYA
April 1998
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TABLE OF CONTENTS
ACKNOWLEDGEMENTS .................................................................................................................................... iv
ABBREVIATIONS AND ACRONYMS ............................................................................................................... v
CHAPTER ONE: BACKGROUND ...................................................................................................................... 1
INTRODUCTION .................................................................................................................................................................... 1
TERMS OF REFERENCE ..................................................................................................................................................... 1
STUDY METHODOLOGY ................................................................................................................................................... 3
OUTLINE OF THE REPORT .............................................................................................................................................. 4
CHAPTER 2: SOCIOECONOMIC PROFILE OF BOMET DISTRICT ..................................................... 5
BOMET DISTRICT IN THE NATIONAL CONTEXT ................................................................................................ 5
CLIMATE AND SOILS OF THE DISTRICT ................................................................................................................... 6
THE PEOPLE............................................................................................................................................................................ 7
WELFARE AND THE DISTRIBUTION OF INCOME ............................................................................................... 8
THE MYTH OF KERICHO .................................................................................................................................................. 8
CHAPTER 3: LELAITICH IN THE BOMET CONTEXT............................................................................ 10
LOCATION AND SIZE ....................................................................................................................................................... 10
AGRICULTURAL PRODUCTION ................................................................................................................................... 10
EDUCATION .......................................................................................................................................................................... 13
HEALTH ................................................................................................................................................................................... 16
CHAPTER 4: SURVEY DESIGN AND IMPLEMENTATION .................................................................. 18
SAMPLE DESIGN AND SELECTION ........................................................................................................................... 18
ESTIMATION PROCEDURES .......................................................................................................................................... 18
AAK MEETING TO DISCUSS THE QUESTIONNAIRE ......................................................................................... 19
PRE-TESTS .............................................................................................................................................................................. 20
FIELDWORK .......................................................................................................................................................................... 21
SUGGESTIONS FOR FUTURE IMPROVEMENTS IN SURVEY DESIGN ....................................................... 22
DATA ENTRY AND PROCESSING ............................................................................................................................... 24
CHAPTER 5: RESULTS OF THE FIELD SURVEY....................................................................................... 25
RESPONSE RATES ............................................................................................................................................................... 25
HOUSEHOLD AND DEMOGRAPHIC CHARACTERISTICS ................................................................................ 25
CHILD WELFARE ................................................................................................................................................................. 28
HOUSEHOLD AMENITIES .............................................................................................................................................. 28
AGRICULTURAL PRODUCTION ................................................................................................................................... 29
SOURCES OF HOUSEHOLD INCOME ........................................................................................................................ 31
LAND OWNERSHIP AND ACCESS ............................................................................................................................... 32
HOUSEHOLD CONSUMPTION PATTERNS ............................................................................................................. 32
CHAPTER 6: OVERVIEW, FINDINGS AND RECOMMENDATIONS ................................................ 35
OVERVIEW ............................................................................................................................................................................. 35
ACCURACY OF SURVEY RESULTS ............................................................................................................................... 35
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SUMMARY OF THE MAIN FINDINGS ........................................................................................................................ 36
ACTIVITIES UNDERTAKEN TO-DATE ..................................................................................................................... 38
RECOMMENDATIONS ...................................................................................................................................................... 39
CHALLENGES AND CONSTRAINTS ........................................................................................................................... 40
REFERENCES .......................................................................................................................................................... 42
LIST OF ENUMERATORS ................................................................................................................................... 46
PEOPLE CONTACTED ........................................................................................................................................ 47
STATISTICAL APPENDIX .................................................................................................................................. 48
ENUMERATORS’ REFERENCE MANUAL ................................................................................................... 94
SURVEY QUESTIONNAIRES .......................................................................................................................... 120
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ACKNOWLEDGEMENTS This report presents the findings of a detailed household survey undertaken in Lelaitich location of Sigor division, Bomet district, during December 1997. The survey covered 225 households in three sub-locations, namely, Lelaitich, Kapsabul and Lugumek. The main objective of the baseline survey was to collect information from households so as to give insights into the socioeconomic profile of the population, and identify causes of poverty and the coping mechanisms adopted by households and the community. The research was funded by ACTIONAID-Kenya (AAK). I thank Mercy Karanja, Project Coordinator/ Bomet Development Initiative, and her staff for the support in the exercise. The support of Anthony Mwaniki, former Director, Central Bureau of Statistics, is gratefully acknowledged.
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ABBREVIATIONS AND ACRONYMS AAK ACTIONAID-Kenya AEZ Agro-Ecological Zone APC Assistant Programme Coordinator BCG Bacille Calmette Guerin CBO Community Based Organization CBS Central Bureau of Statistics CDW Community Development Worker CORP Community Resource Person DDO District Development Officer DI Development Initiative DPT Diphtheria, Pertussis and Tetanus ECD Early Childhood Development Ha Hectare HCDA Horticultural Crops Development Authority IGA Income Generating Activity KAP Knowledge, Attitudes and Practices KARI Kenya Agricultural Research Institute KCC Kenya Cooperative Creameries KEPI Kenya Expanded Programme on Immunization KTBH Kenya Top Bar Hive KTDA Kenya Tea Development Authority LH Lower Highland (agro-ecological zone) MCH Maternal Child Health MOH Ministry of Health NCPB National Cereals and Produce Board NGO Nongovernmental organization OTC Over the Counter PC Programme Coordinator PPA Participatory Poverty Assessment PRA Participatory Rural Appraisal PTA Parents-Teachers Association RDA Recommended Daily Allowance RRA Rapid Rural Appraisal SPSS Statistical Package for the Social Sciences TBA Traditional Birth Attendant UM Upper Midland (agro-ecological zone) URTI Upper Respiratory Tract Infection
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CHAPTER ONE: BACKGROUND
INTRODUCTION 1.1. In January 1996, AAK conducted spatial analysis on poverty and vulnerability in Kenya using secondary data. The study was in to response AAK’s desire to open up new programme areas since the bulk of its resources were previously devoted to Eastern province1. The study identified North Eastern province and west Rift Valley as prone to vulnerability due to drought and its effect on livestock production; eastern parts of Coast province suffer from harsh climatic conditions; while Western and Nyanza provinces have high population densities and poor returns from the industrial crops grown in the region e.g. sugar. Poverty in the vulnerable districts of Coast, Rift Valley and North Eastern provinces also manifests itself in low literacy and poor nutrition; and in low nutrition status in Nyanza and Western provinces. The study identified Bomet as one of the disadvantaged districts in the country that merited AAK intervention. In May 1996, AAK undertook more detailed studies of the districts identified for AAK intervention which identified Sigor division as the most disadvantaged in the district. 1.2. In 1997, AAK expanded into the new districts. The expansion into new areas was expected to increase the legitimacy of the organization when speaking out on national issues that impact on poverty eradication. The expansion in area coverage coincided with a shift in the organization’s programme approach from service delivery to community empowerment, which aimed to place poor and marginalized people in the driving seat of development process. A community empowerment approach increases the capability of poor people to critically analyze, make decisions and organize themselves to claim rights as the key to poverty eradication. AAK developed the Development Initiative (DI) model to propel this approach forward at the grassroots level. The DI operational areas are small, usually covering 1-2 administrative locations with a population of up to 20,000. Each DI has an optimum staff level of three persons, with no support staff. 1.3. AAK Bomet Development Initiative (DI) was started in Lelaitich location of Sigor Division in July 1996. In October 1996, the Bomet DI team conducted a Rapid Rural Appraisal (RRA) in Lelaitich location in order to collect primary data from community members on workable approaches for poverty reduction and empowerment and advocacy in favour of the poor, especially women and children. TERMS OF REFERENCE 1.4. The 1997 Bomet Appraisal Document acknowledges that “some findings that beg more answers will be addressed through baseline studies as the DI establishes itself”. There was therefore need to conduct further analysis on some developmental issues identified in the RRA, particularly at the household level, in order to isolate factors that create and sustain mass poverty, and to recommend viable activities that AAK can undertake in collaboration with the community and other partners. The main objectives of this study are: (a) To provide information required for targeting interventions on critical development issues in the
operational area; (b) To empower the DI staff with information that is required for participatory planning of
development initiatives supported by AAK; 1 Kenya has a hierarchically nested administrative organization, from nation, province, district, division, location, to sub-location. The hierarchically nested administrative organization of government is normally referred to as the provincial administration. It starts from the President all the way to the assistant chief at the sub-location level.
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(c) To collect from households/ community/ institutions and analyze existing data which would
form a benchmark for subsequent monitoring and evaluation of the impact of DI on the population, especially on vulnerable groups;
(d) To inquire into methods adopted by the population so as to cope with the constraints arising
from poverty and social exclusion; and (e) To draw conclusions and make recommendations on possible areas of intervention and strategic
objectives AAK should pursue to make an impact in the area. 1.5. In order to meet the above objectives, the study was supposed to focus on the following areas:
Household and Demographic Analysis - Household size and composition, age and sex distribution, marital status, and headship - Occupational status by gender - Literacy - Migratory practices
Sources and Systems of Livelihoods - Household living conditions and available material resources - Resource availability, access, distribution and control by gender - Sources of household income by season and gender - Household expenditure on food and non-food items - Household income and expenditure control - Basic household resource requirements - Nutritional status - Land use patterns and farming practices
Community Organization and Institutions - Community institutions - Community participation in self-help - Types of community organizations and their use in socioeconomic development
Education - Literacy levels - School access, enrolment, dropout and completion rates by gender and age-group - Reasons for dropping out by gender and age group - Home and school variables/ factors that inhibit access and retention in schools - Perception of pupils and parents on the benefits and cost of staying in school - Magnitude and effect of early marriages and pregnancies on girls’ education - Recommend strategies to raise educational standards in the area
Health, Water and Environmental Sanitation - Morbidity by type and age - Immunization coverage and prevalence of disabilities - Household coping mechanisms and options for treatment - Sources of water including safe water coverage by technology
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- Water collection, storage, quality and reliability - Water point ownership and control - Water point operation and maintenance - Propose appropriate technological options for construction of latrine and hand-dug
wells - Knowledge, attitudes and practices (KAP) on environmental sanitation - Waste disposal methods including latrine coverage, utilization and maintenance by
technology - Constraints in latrine construction
Development and Advocacy Issues - Identification and categorization of resources needed to support basic human goals - Resource potential of the DI area - Problems facing women with respect to access to land, labour and capital, control over
resources and access to benefits of development - Socioeconomic development problems affecting the participation of the DI households
in ownership, management and control of resources as well as self-help and income generating initiatives
- Recommend realistic DI interventions, strategies and resources required to promote household welfare and sustainable development
Organizational Considerations - From the organizational perspective, indicate the resources required to implement the
suggested recommendations in all the three sectors of food security, education and health, including staffing, staff training as well as logistics, taking due recognition of existing actors.
STUDY METHODOLOGY 1.6. The methodology combines a variety of approaches to collect household and community variables in fulfilment of the terms of reference. Since secondary data is rather scanty especially specific to Lelaitich location, the study faced the moral dilemma in research, i.e. if all the necessary data is available from secondary sources, the research would not be necessary, while lack of the same data makes it difficult to judge the validity of findings from the research activity. The study uses secondary data to create a resource profile for the whole of Bomet district. The analysis of district-level data is useful for two reasons. First, Lelaitich location is spatially nested within Bomet district and Sigor division, and the basic unit of Government budgetary planning and expenditure is the district. It is therefore important to understand the resource endowment and Government resources devoted to Lelaitich location relative to other areas in the district. Secondly, the development of the location will hinge on AAK’s support from Government at the district-level, and there is therefore need for district-level Government heads of departments to appreciate the need for increased resource allocation to Lelaitich location. 1.7. At the location level, data was gathered using three main methods. First, secondary data on health, education, water and livelihoods was gathered from Government line ministries, community members, and facilities (health facilities and schools). Second, a structured questionnaire was used to collect household-level variables on demographics, housing and living conditions, poverty and livelihoods, education and literacy, and household access to health and water and sanitation. Third, interviews with community members using semi-structured questionnaires were used to solicit qualitative information on, say, distribution of power and resources within households, community organizations and institutions, reasons for school dropouts, and pregnancy and early marriages.
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OUTLINE OF THE REPORT 1.8. The report is divided into five chapters. Chapter 2 gives a socioeconomic profile of Bomet district within the national context. Chapter 3 gives a socioeconomic profile of Lelaitich location in relation to the district, with emphasis on the degree of social exclusion of the study area relative to other areas in the district and the causal factors that explain this phenomenon. The profile of Lelaitich location is based on secondary data from Government and the community. 1.9. Chapter 4 focuses on the survey instruments used to collect quantitative data from households e.g. survey design and estimation procedures used in generating aggregates from individual questionnaires. Chapter 5 presents the results of the household survey, while chapter 6 gives conclusions and recommendations based on both qualitative and quantitative data collected during the entire study process. The last part of the report consists of (a) statistical appendix based on Government data and the results of the household budget survey, and (b) survey instruments (enumerators’ reference manual and questionnaires).
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CHAPTER 2: SOCIOECONOMIC PROFILE OF BOMET DISTRICT BOMET DISTRICT IN THE NATIONAL CONTEXT 2.1. Bomet district was created in 1992 as a result of the division of the former Kericho district. It is bordered by five districts, namely, Nakuru to the east, Kericho to the northwest, Nyamira to the west, Trans-Mara to the southwest, and Narok to the south and southeast. The district lies approximately between latitudes 0o-29’ and 1o-03’ south of the equator and between longitudes 35o-05’ and 35o-35’ east. The boundaries of Bomet district are given in The Districts and Provinces Act, 1992 (Kenya Gazette Supplement No 53, 26 June 1992, pages 124-5). 2.2. There is scant administrative and survey data specific to Bomet district since time series data is under the former Kericho district. The former Kericho district is known for its large share of tea production based on the large farm sector. However, household survey data portray Kericho as a poor district due to capital flight arising from the large farm sector, and the fact that some labour in the tea estates comes from outside of the district especially from Nyanza province. For example, the 1992 National Household Welfare Monitoring Survey conducted by the Central Bureau of Statistics (CBS) ranked Kericho as one of the poor districts in Kenya, mainly due to the large share of plantation sector in agricultural production and the inclusion of the now Bomet district which is poorer than the new Kericho district (Mukui, 1994). 2.3. As stated in Mukui (1994):
Kericho/ Bomet district consistently exhibited higher poverty levels than envisioned, both in 1982 and 1992. According to the 1989-93 Kericho District Development Plan, the district produces adequate food for consumption and surplus for sale outside the district. There are at least two possible explanations for Kericho’s poverty statistics. First, migrant labour in the plantations may have low levels of consumption within the district due to transfers to home districts. Second, the survey instruments may not have imputed the true value of free housing, water and electricity and subsidized medical care, education and recreation (sporting facilities) for the responding households in the plantations. A district-level survey focusing on production, consumption, migration and resource transfers need to be undertaken before any firm conclusions can be made about poverty in Kericho district. An initial reference point would be to empirically test the proposals suggested by Davies (1987) in her study of the direct and indirect links between Kericho tea plantations and the immediate rural economy (Kericho) and sources of migrant labour (mainly Nyanza province).
2.4. The first participatory poverty assessment (PPA) was undertaken by the Government during February-April 1994 to complement statistical studies of poverty in Kenya. The PPA covered selected clusters in Bomet, Busia, Kisumu, Kitui, Kwale, Nyamira, Mandera and urban Nairobi. However, the findings of the PPA are inadequate for comparison of the socioeconomic fortunes of Bomet in relation to other parts of Kenya because it was a qualitative survey; was not nationally representative as it covered a limited number of districts; and the households covered in each district were few. In general, wealth ranking used in the PPA measures relative poverty, which is only of relevance to the immediate environment in which it is conducted, and the findings cannot therefore be used for interregional comparisons. 2.5. The second National Welfare Monitoring and Evaluation Survey (WMS2) was conducted by CBS in 1994 and included Bomet as an independent strata from Kericho. The results of the survey showed that Bomet literacy rate for persons aged 15 years and above (73.8%) was around the national mean
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(74.8%), with 84.0% for males (national: 82.8%) and 37.1% for females (national: 32.6%). Child welfare indicators e.g. immunization coverage, average length of breastfeeding and number of months children exclusively breastfed were close to the national average, while indicator of severe protein-energy malnutrition as measured by weight-for-height (wasting) was better than the national average. The reported Bomet mean monthly household income was Shs 11,265.4, compared with a national average of Shs 8,508.0 for rural Kenya and Shs 9,696.0 for the whole of Kenya including urban areas. CLIMATE AND SOILS OF THE DISTRICT 2.6. The long-term mean rainfall in the district is 1885.4 mm. The district receives rainfall throughout the year with peaks in March-May (long rains) and August-October (short rains). Within the district, there are significant variations in rainfall. Relatively higher rainfall (over 1600 mm) is recorded in lower midland zone covering Konoin, Kimulot, Sotik, north-eastern part of Bomet Central, and upper parts of Longisa. At the other extreme, the southwest part of the district covering Kaboson, Sigor and Longisa is characterized by sub-humid climate. The altitude is 900-1850 mm with annual rainfall in the range of 450 mm in the extreme south to 1100 mm in the upper zone. The zone is important for maize, sorghum/ millet and livestock farming. The high rainfall in the district is both a boon and bane as it leads to high acidity and hard water in the upper plains. Wet conditions are also a constraint to efficient transportation both in areas with well drained soils and areas with poorly drained soils. However, since rain measurements are taken in Kimulot, Konoin and Sotik and do not include the lower, drier plains, the reported district mean annual rainfall is higher than actual. 2.7. The district can be divided into two main agro-ecological zones (AEZ), namely, lower highland (LH) and upper midland (UM). AEZ LH1 found in the north-eastern tip of the district is the tea and dairy zone with permanent cropping facilities, i.e. two variable cropping seasons with the first rains starting in February and the second rains starting around the end of July. LH2 is the wheat, maize and pyrethrum zone with very long cropping season, with the first rains around March and the second rains starting around end of July. The upper midland (UM) zone is suitable for tea and coffee. In some portions, both tea and coffee can be grown, while in others only coffee is grown. The zone is characterized by a long cropping season. In the marginal portions (UM4 and UM5) where Lelaitich falls, economic activities include growing of sorghum, maize and livestock rearing. 2.8. There are three major types of soils in the district, namely, clay (43.6% of land outside forest reserves), loamy (10.9%) and black cotton soils (45.5%). Soils are generally fertile with altitude, temperature and rainfall as the main determinants of farming practices in each area. The details of soil and agro-ecological zones of Kericho and Bomet are given in a report published by the Ministry of Agriculture (Kenya, 1987). The results of the farm trial site situated at Chebunyo in the neighbouring Kaboson location are fairly representative of Lelaitich location. 2.9. The main water sources in Bomet are rivers, streams and springs. In the upper parts of the district, high and reliable rainfall makes these sources dependable, while seasonal shortage is experienced in the lower plains. The quality of water is low, mainly due to poor sanitary conditions and high use of fertilizers and agro-chemicals especially in the tea and pyrethrum plantations. Bomet town has inadequate, untreated water and the sewage drains on the surface towards Nyangores River. The latter is the source of water for Sigor-Longisa water supply which is supplied untreated. There is therefore recycling of sewage (though to a smaller extent in Bomet town since the piped water from Nyangores river is treated) and spreading it untreated to areas in the lower plains of Sigor and Longisa divisions. The clay soils do not allow water to percolate, and the toilets therefore overflow and pour the sludge on the land, thus exacerbating environmental sanitation during the rainy season.
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THE PEOPLE 2.10. The population of the district was 437,492 in 1989 and was estimated at 556,160 in 1997. The district has a youthful population with over 30% under nine years, which leads to high dependency ratios and the consequential high demand for food and social services e.g. health and education. 2.11. The main ethnic group in both Kericho and Bomet districts is the Kipsigis. According to historians, the Kipsigis as a tribe is a mixture of Bantu and non-Bantu blood. The designation ‘Kipsigis’ includes persons of foreign extraction. According to Ochieng’ (1975), “people of Gusii extraction constitute about two-thirds of present-day Kipsigis society, others being Okiek (Kalenjin element), Turkana, Luo, Maragoli, Tugen, Keiyo, Nandi, Sirikwa and Maasai extraction”. Toweett (1979) argues that “if the Kipsigis divided themselves into those tribal units, there would be no one else to be called a Kipsigis”. The present ‘boundedness’ of the Kipsigis is a product that was not there in the remote past. The final force of integration and ethnic consciousness was the establishment of British colonial rule. As Mwanzi (1977) states “by placing all the Kipsigis within fixed boundaries, colonialism helped to unify them”. The incorporation of Kipsigis as a political and ethnic sub-unit within the Kalenjin is a more recent phenomenon. The fusion of the Kalenjin sub-tribes, despite lack of common ancestry, made them graduate to a “big tribe” status, which was given official recognition in the 1989 Population and Housing Census by being lumped together as one ethnic group. The Kalenjin elites have used this agglomeration for political expediency, but the Kipsigis peasantry is only close to the neighbouring Kalenjin-Nandi sub-tribe. 2.12. Traditionally, all the people wanted from the land were grass and millet. The Kipsigis kept cattle, goats and sheep for meat and milk. Cattle had a special place in the Kipsigis culture as they were the mode of payment of bride price, and hero worship was based on success in institutionalized raiding of cattle from other ethnic groups. Cattle were held in high esteem and for this reason could not be involved in work such as ploughing. This is the reason Kipsigis reacted strongly when ploughing by oxen was introduced in the early 1900s. The donkey is a latter development among the Kipsigis and it is believed to have been introduced by the Maasai where it was in turn introduced by Swahili traders. To this day, the donkey has become the chief means of transport and a woman’s best friend in the interior of Kipsigis country where the roads are too poor for motor vehicles. 2.13. The Kipsigis people knew more than ten types of millet, the crop calendar, millet food preparation, and the making of millet liquor. The brew was used for ceremonial purposes related to the rites of passage (mainly birth, circumcision and marriage) or as labour wage for helping in harvesting millet or fencing a garden. They practised shifting cultivation, where bushes were burnt after cultivation and land was not cultivated for more than three consecutive years. The belief that millet is best grown in new land (as opposed to land which has been under cultivation for a long time) persists to-date. Sorghum was later introduced from Kuria country. Honey collection was also an occupation as people could make their own beehives or collect wild honey in the thickly forested areas. They never planted fruits although they used to eat wild fruits. Fowls and hens were introduced recently. The traditional farming technology used elephant ribs until the hoe was introduced by Gusii blacksmiths. The famines recurring in the history of Kipsigis culture illustrate the inadequacy of farming practices, a phenomenon which Mwanzi (1977) states was partly reinforced by Kipsigis male prejudice against manual labour. The dislike for manual labour persists as the tea estates and factories mainly source their labour from the Gusii and Luo communities; and artisans within Kipsigis country (e.g. construction workers and motor vehicle repairers) are still drawn from the abovementioned communities. 2.14. Gender differentiation among the Kipsigis is deeply embedded in their culture and history. Somok (three) is a female number e.g. clapping three times when a girl is born, or a mother staying in the house for three days after giving birth to a baby girl. Ang’an (four) is a masculine number, which is both sacred and a show of strength as it existed in religious rites and rites concerning baby boys and adult males. A baby born to an unwed mother was usually killed as it was considered unclean. Initiation rites for both males and females extended over a period of months. Kipsigis, especially in the lower plains where
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Lelaitich is situated, usually perform the initiation rites in November and December – the longest school holiday of the year. This is mainly due to the educational system of three months of school followed by a month of vacation, and partly due to Government regulations which do not allow initiation camps to start before schools close or to extend beyond vacation time. The conflict between school and initiation calendars continues to have profound impact on education, especially of the girl-child. Following marriage, a man was allowed to beat his wife if she displeased him, but the wife was not allowed to beat her husband. Polygamy was widespread as it was taken as a sign of prestige and wealth2, while wife-inheritance (kipkondit) by a brother of the diseased is still practised (see also, Orchadson, 1931). It is traditionally allowed for an old childless widow to take a wife. The widow goes through the same procedure as a man in taking a wife. A husband is found for this “wife”, and children of this union are the children of the widow and her deceased husband (Orchadson, 1931). WELFARE AND THE DISTRIBUTION OF INCOME 2.15. Table 3 shows that the district mean income per capita in 1995 was Shs 10,719, which confirms the district location in a high potential area of the country. The figures for 1992 exclude income from business; the 1996 data excludes income from business and value of marketed livestock products; while data for all years does not include subsistence and informal sector activities. Five divisions, located in the marginal and sub-marginal parts of the district, have per capita income below the mean. “Wealthy” divisions are Konoin, Kimulot and Bomet Central, while Ndanai was the poorest. The poorer divisions (Ndanai, Longisa, Sigor and Siongiroi) are also highly vulnerable to drought. The data should, however, be interpreted with caution due to omissions and the fact that it is based on production rather than household disposable income, and does not therefore factor in capital inflows and capital flight. THE MYTH OF KERICHO 2.16. The residents of the Kipsigis country, as well as the rest of Kenya, believe that Kericho and Bomet are rich districts. However, a significant proportion of the residents do not enjoy its bounty. This is partly due to the existence of the plantation sector and the fact that the generalization about the land of milk and honey is based on observations made in the current Kericho district and the upper parts of Bomet district. The Bomet plantation sector represents about 75% of total tea production. This translates to high capital flight since the estates are foreign-owned and the workers in the tea estates are mainly immigrants from outside the districts (mainly from Gusii and Luo countries). Beginning around July 1997, some small tea growers in Kericho and Bomet began to sell green tea to middlemen at about half the price received by selling through the Kenya Tea Development Authority (KTDA). This implies that the fixed costs of running the KTDA-managed tea factories will be absorbed by lower tea deliveries, and subsequently lower the returns even for those who continue to deliver to the factories. In addition, the activity will increase capital flight from the two districts. 2.17. Before sub-division of the “old” Kericho district in 1992, most of Government resources and private sector investments were directed to areas which cover the “new” Kericho and the productive upper plains of Bomet. The lower plains of Bomet were excluded from development and human interaction with the outside world. Since the neglected areas were also far from eyes in the productive parts of Kericho and the rest of the Kenya, the myth of a rich Kericho persists regardless of the results of household-based surveys which measure household disposable income rather than district production. 2.18. Within Bomet district, the upper and lower plains do not have close interactions at human and 2 As observed by Borgerhoff-Mulder (1987; 1990), rich Kipsigis men have more cattle and more wives, as being the second wife of a man with plenty of cattle is a better fate than being the first wife of a poor man. However, the author does say anything about the views of the first wife. See also, Ridley (1993) and White (1989).
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economic levels. A big proportion of Government personnel at the district headquarters have not visited remote locations e.g. Lelaitich, which has affected the movement of Government resources to the poor areas. This is reflected in poor provision of social services (e.g. education and health), and the relative scarcity of secondary data from official sources on the remote locations of Bomet. The right hand does not know the left hand exists. There is, for example, no weather station in the lower plains, which leads to overstatement of the district mean annual rainfall, and thus perpetuate the myth of Kericho. 2.19. The apparent lack of exposure of district Government personnel to the living conditions in the lower plains is partly due to lack of transport to traverse the whole district, and the fact that most Government employees come from Bomet upper plains, Kericho district, and outside of Kipsigis country. Although Government development plans give a rosy picture of the district, there is a case for ACTIONAID-Kenya support to the office of the District Development Officer (DDO) to prepare a spatially detailed and realistic district profile.
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CHAPTER 3: LELAITICH IN THE BOMET CONTEXT
3.1. This chapter gives an overview of Lelaitich sub-location in comparison with the rest of Bomet district. The information used was obtained from secondary sources e.g. views and data provided by Government departments, and discussions with community leaders in the district. LOCATION AND SIZE 3.2. Lelaitich location borders Narok district to the southeast, Kaboson location to the south, Sigor location to both north and west, and Longisa division to the northeast. River Amalo running along the Bomet-Narok border is the only perennial river, and is augmented by two seasonal streams (Lelaitich and Cheptare). Lelaitich experiences semi-arid climatic conditions characterized by low, unreliable rainfall. The location lies within the upper-midland agro-ecological zone (UM4 and UM5) which at best suits maize growing, livestock (beef cattle and goats), sorghum, millet and sunflower. The vegetation comprises mainly of thorn trees and shrubs. 3.3. The location is administered by a chief and three assistant chiefs each in charge of one of the constituent sub-locations, namely, Lelaitich, Kapsabul and Lugumek. The names of the sub-locations and villages give clues about the flora and fauna that used to be abundant in the recent past e.g. fig tree (simotwet). The population of Lelaitich location (then Lelaitich sub-location) was 5,888 according to the 1989 Population and Housing Census. AGRICULTURAL PRODUCTION Crop Production 3.4. The main crops grown in the district are tea, coffee, pyrethrum, maize and English potatoes. Kericho and Bomet are known for tea production. The district produces about 43 million kg of tea per year, which is mainly from the upper plains (Sotik, Bomet Central, Konoin and Kimulot). Coffee is mainly produced in Sotik division (about 40 ha), although limited growing is undertaken in Sigor and Longisa. Pyrethrum is mainly grown in Bomet Central (about 80% of district total), while the balance comes from Longisa. 3.5. In 1996, the district produced an estimated 901,789 90-kg bags of maize, with an average output per acre of 8 bags in the upper zones and 3 bags in the lower zones. Some farmers in the lower zones experienced total crop failure. Maize grown in the upper plains is sold to middlemen, private millers and the National Cereals and Produce Board (NCPB), while the lower zones are maize-deficit areas. Potatoes are mainly grown in Bomet Central and Longisa. Other than Kimulot where most productive land is under tea, there is no severe food stress in the upper zone. 3.6. The lower zones experienced crop failures during 1993-97, while the average productivity of maize has fallen to below 3 bags per acre. One of the factors is planting of uncertified seeds or wrong varieties of certified seeds, i.e. the long-maturity 6-series rather than the short-maturity 5-series. The agricultural extension staff estimated that 70% of maize seed planted in Lelaitich was uncertified. The collapse of maize prices following the abolition of retail price controls in December 1993 made it uneconomical to plant certified seeds. Although the agricultural extension staff expressed frustration at the failure of the community to follow expert advice, the farmers stated that both types of certified seeds (6-series and 5-series) are uneconomical. For example, there has been virtually no harvest in Lelaitich for three consecutive years. However, consumption patterns in favour of maize and the households’ preoccupation with self-sufficiency has made farmers continue planting maize.
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3.7. The Government crop production report for 1997 indicates that area under maize in Lelaitich location dropped from 1,120 ha in 1996 to 690 ha in 1997, with an average output per ha of 0.23 tons, and a total output of 162 tons (1,800 bags). Other important crops in Lelaitich include sorghum (34 ha in 1997), beans (102 ha), finger millet (5 ha), cabbages (6 ha), kales (7 ha), tomatoes (8 ha) and sweet potatoes (18 ha). In Lelaitich, maize suffers from pests: elephants and monkeys (especially in Lugumek), stock-borer, weevils, and smut diseases. 3.8. Most of the Government extension and research activities are concentrated in the upper zone and Longisa. Examples include the Kenya Agricultural Research Institute (KARI) Adaptive Research project mainly covering maize, sorghum/ millet, roots and tubers, beans and horticulture; and a farm management survey which covered Longisa. Due to lack of study on farming practises, the Ministry of Agriculture has no Farm Management Guidelines covering Lelaitich location, and there is need for AAK to investigate possible support to Sigor division agricultural staff to fill this gap. 3.9. Ironically, the high potential areas also have “reasonable” use of fertilizer compared with the lower marginal zones. In the lower zones, namely, Chepalungu, Siongiroi, Sigor and lower Longisa, soil-burning after cultivation is still practised. Traditionally, the only field crop grown was millet (since it was resistant to weevils) before white sorghum was introduced from the Kuria country and maize by the colonial government around 1912. Millet was rarely sown on old land as the crop was liable to fungoid diseases and likes plenty of potash (Orchardson, 1961). After land was cleared, the clearing was burnt. The tradition of planting millet in virgin land and general burning of bush clearings after cultivation persists up-to-today. Agricultural extension staff should therefore focus on sensitizing the community on the value of incorporating crop residues in improving and maintaining soil fertility and in reducing soil erosion. Sorghum is not popular since it makes soil infertile and is eaten by birds, while millet production is limited due to the tradition of planting on virgin land. However, millet could do well on old land if there was supplementation with potash fertilizers. 3.10. Famine relief has only been common in recent years (1994-97) due to declining agricultural production in the lower zone. Famine relief is mainly centred in Sigor, Longisa and Siongiroi, and some pockets of poverty in Bomet Central, Ndanai and Sotik. Famine relief has been in the form of maize for consumption, certified maize seeds as a way of introducing the seeds appropriate to the lower zones (5-series), beans, and seed-beans. The 1993 drought was so adverse that some farmers could not afford to purchase inputs for the 1994 planting season. The Government therefore decided to give some famine relief in the form agricultural inputs e.g. seeds. 3.11. The attempt to popularize 5-series in the lower zones has not been successful since neither 5-series nor 6-series appear to cope with the soils and climate of lower zones, especially Lelaitich. Despite the fact the 5-series mature faster than the 6-series, it is common in Bomet, as in many parts of Kenya, for farmers to prefer the 6-series due to the big grains. In the lower plains, there are no resident commercial suppliers of certified seed, and farmers are therefore forced to travel to Bomet town, 40 km away. Since the bean-seeds given as food relief are machine-dried, some farmers who plant them without prior knowledge that they can’t sprout complained that the Government personnel involved in distribution should inform them in advance. Such cases were reported in November 1997. Every household in Lelaitich received about 90-kg of maize for food in 1997. 3.12. Some farmers in Lelaitich experimented with growing sunflower around 1989, but the venture collapsed due to lack of a ready market. In the past, Sigor division was a major producer of onions which was marketed through the Horticultural Crops Development Authority (HCDA), but there is currently little domestic demand while transport costs to outside markets are prohibitive due to poor state of the road network. A few farmers grow oranges, but there is low domestic demand while roads to outside markets are impassable in the wet season. Most farmers are not used to growing vegetables, including farmers bordering Amalo river.
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Livestock Production 3.13. The district has a high production of milk especially in the upper plains. Out of the estimated 174,000 dairy and high-grade dairy crosses, only an estimated 1,500 were in Sigor division, while Lelaitich location has no pure grade at all. Without effective tick control and nearer distances to water points, it is uneconomical to keep grade cattle in the marginal zones, while good fodder cannot grow due to low and unreliable rainfall. However, Sigor division holds an estimated 40,000 of the 206,000 zebu cattle in the district. Milk from the upper plains is sold to state-owned Kenya Cooperative Creameries - KCC (16 million kg in 1996) and private processors, while milk from the lower plains is for family use and sale to neighbours and local market centres. 3.14. Beef production is not a specialized industry in the district. The beef industry is supported by a sizeable zebu population in lower zones, and steers and culls from the dairy industry in the upper zones. Cattle for slaughter are sold in sale yards, some transported to Nairobi and neighbouring districts of Kisumu and Kericho, while the rest are slaughtered within the district. The sale yards closest to Lelaitich are Chebunyo in Siongiroi and Mulot in Longisa. The district also has a sizeable population of meat goats (about 80,000) and sheep (about 110,000). Dairy goats are rare as the inhabitants do not consider goats and sheep as sources of milk. The pig industry is almost nonexistent due to market and cultural factors as people have little preference for pork. It was traditionally a taboo to eat rabbits, but the culture is easing with time. 3.15. All cattle dips have been managed by local committees since Government divested itself of the responsibility in 1992. An estimated 65% of the cattle dips in Bomet are not operational. Hand-spraying is the major method of tick control, which is not done regularly by some farmers, nor is it effectively carried out. Out of 14 dips in Sigor division, only six were functional; and only one in Lelaitich location. Some community members reported that the dips handed over by the Government to the communities were too wide, which implies uneconomical application of acaricide3. However, livestock extension staff claimed that the width of a dip only affects the amount of acaricide used in the initial mix, but the amounts used in replenishment are the same. Livestock travel far to drink water (mainly Amalo river since tributaries are too salty); hence pick ticks on the way. The incidence of tick-borne diseases e.g. East Coast fever and True Gall-sickness (anaplasmosis) is high. 3.16. Poultry keeping consist mainly of birds that fend for themselves (free range) with supplementation of grain feeding, and there are only few commercial rearing for eggs or meat. The industry is relatively popular in the lower zones where few other enterprises thrive, but suffers from serious problems of egg marketing and high incidence of chicken diseases. Agricultural extension focusing on chicken is negligible. District government personnel stated that they did not know the role of poultry in the economy of the lower plains until 1994-5 when the Newcastle Disease (which can be controlled by vaccination) and coccidiosis4 almost wiped out chicken in Sigor division. 3.17. Although the inhabitants of the district were traditionally beekeepers, beekeeping is not as widespread as expected. The district boasts of only 1,200 Kenya Top Bar Hives (KTBH), about 7,500 traditional log-hives, and crude honey production of 74,000 kg. The market is underdeveloped due to lack of organized honey marketing, absence of honey refinery, high cost of KTBH, and low number of improved bee-hives. The lower zones and areas adjacent to Mau forest in the higher zones have a diversity of bee-forage plants. Crude honey is sold locally and in local market centres. Lelaitich location is honey-poor. 3.18. The nearest veterinary dawa shop is in Sigor, while Government vaccination efforts were considered inadequate. Cattle continue to suffer from tick-borne and tsetse-transmitted (e.g. fly-bone) diseases, and worms (due to dams). Sheep and goats were reported to mostly suffer from worms and 3 Acaricides are pesticides that kill members of the acari group, which includes ticks and mites. 4 Coccidia are specific to chickens and cannot infect other types of birds or mammals.
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pneumonia. In the context of food security, cattle are inappropriate in redressing short-term food and income stress due to general unwillingness to sell. Among livestock, only goats are used to alleviate short-term stress on livelihoods (sale or home consumption). Donkeys are used in ploughing; and carrying water, maize and firewood. EDUCATION Early Childhood Development 3.19. Of the 449 pre-schools in Bomet district, 367 (81.7%) were sponsored by parents/ community, 72 (16.0%) were by local authorities, and the remaining ten were private nurseries or sponsored by religious organizations. There is almost gender parity in pre-school enrolment in the whole district other than Sigor division (with 1,451 boys and 752 girls in 1995, and 1,650 boys and 812 girls in 1996). The parents of pre-school children in the community schools shoulder the management and financing of the pre-schools, while local authorities meet the cost of teachers in the pre-schools they sponsor. All community and local authority pre-schools are attached to primary schools. The pre-schools are therefore normally managed by primary school committees. The whole district had two male pre-school teachers, one trained and the other untrained. This phenomenon, which exists in other parts of Kenya, is associated with the fact that women are child caregivers and parents feel freer when their children are in the hands of females, thus the preference for female teachers. As in the rest of Kenya, pre-school teachers are underpaid, which might have contributed to pre-school teaching as a “she” career. 3.20. The average cost of sending a child to a community or local authority pre-school was Shs 500-800 per year. Fees in community pre-schools are not paid regularly and they therefore normally rely on the parent primary school for chalk, desks, housing and other expendables. Pre-school teachers in community schools receive about Shs 450-850 per month (which normally exclude holidays and is not regular), while those paid by local authorities receive Shs 3,500-6,000. 3.21. Parents mainly send their children to pre-school because it is a pre-requisite for admission to primary school. This was evident from the fact most of the children attend for one year or less. Those who do not send their children to pre-school cite financial difficulties. The main problems facing pre-school education are poor and irregular remuneration of teachers, non-payment of fees, lack of support by parents due to ignorance about the pivotal role of early childhood education on long-term child development, and long distance to pre-school centres which is partly circumvented by reducing school hours to 9 a.m.- 12 noon. 3.22. The eight pre-schools in Lelaitich location are community-sponsored and none has a child-feeding programme. The pre-schools are evenly distributed within the location, with three in Lelaitich sub-location (Nyakichiwa, Lelaitich and Kipsirat), two in Kapsabul (Chemengwa and Kapsabul) and three in Lugumek (Lugumek, Kosia and Kabolwa). The total enrolment in 1997 was 306, comprising of 154 boys and 152 girls. The teachers, who were all females, were either primary school leavers (7) or secondary school leavers (3), making a total of 10 teachers. Out of these, only two are trained. 3.23. Seven of the 8 pre-schools are attached to primary schools while Kipsirat, though community-owned and managed, is on free but private land which has not been formally acquired by the community. The pre-schools have minimal facilities, and are made of timber walls and earth floors. The World-Bank ECD program in Bomet does not include Lelaitich location. There should be focus on provision of facilities and training of ECD teachers. Primary Education 3.24. Education indicators usually include literacy, enrolment and dropout rates, and age-grade mismatch. The literacy rate is defined as the proportion of the population of seven years and over which
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can read or write. The gross primary school enrolment rate is the total number of children regularly attending primary school in the current year divided by the total number of children of primary school age (6-14 years). The net primary school enrolment rate is the total number of children of primary age (6-14 years) currently attending primary school divided by the total number of children of primary school age. The difference between primary school gross and net enrolment rates show the children in primary school but were not of primary school age divided by the number of primary school age children. 3.25. An important education indicator is the dropout rate at various educations levels and the reasons for dropping out, especially reasons connected with the cost of education. The dropout rate is normally defined as the number of children who left school in the current year (excluding those who left due to completion of the relevant education cycle) divided by the total number of children enrolled in the current year (plus the dropouts). The age/grade mismatch shows the relation between age and school grade. If the children started school older than is normally the case, dropped out of school or repeated some grades in the past, the children will find themselves in grades inappropriate for their age. A child with an age/ grade mismatch will observe a different educational experience, in addition to the fact such a child will have additional, but undesirable, adult options compared with classmates e.g. pregnancy, marriage or work. Other things being equal, age/grade mismatch is expected to be positively correlated with dropout rates. 3.26. According to the Bomet District Education Office, there were 146,395 primary school children in 1997, comprising 73,820 boys and 72,575 girls, enrolled in 345 primary schools and with a teaching force of 3,996. Primary Standards 1-7 exhibit close to gender parity in total enrolment but the situation changes dramatically in Standard 8 where boys constitute 57.03% of total enrolment. In terms of progression, time-series data were not available, and only cross-section data for 1997 will be used. However, in situations where school facilities and enrolment are expanding, progression rates based on cross-section data are underestimated. In Bomet district, for every 100 children who enrol in Standard One, only 44 reach Standard Eight, 49 for boys and 39 for girls. The progression rates for Standard One to Seven are 67 and 73 for boys and girls, respectively, which demonstrates sharp rank reversal between Standard Seven and Eight. The data is shown in Table 7. 3.27. In Lelaitich location, there were 1,926 primary school children, comprising 1,014 boys and 912 girls. The progression rates in Lelaitich are slightly lower throughout the primary school cycle than in the entire district. Out of 100 boys in Standard One in 1997, there were only 60 in Standard Seven and 48 in Standard Eight. The comparative rates for girls are 43 in Standard Seven and a low 18 in Standard Eight. Based on the 1997 population estimate (8,790) and ratio of primary school age children to total population in the old Kericho in 1989 (24.3%), the gross enrolment ratio is estimated at 90.2%. 3.28. The high wastage of girls in Bomet is mainly due to age-grade mismatch, with primary school girls getting exposed to adult choices e.g. pregnancy and marriage. Due to late entry to primary school and repetition, most girls get circumcised after Standard Seven. After circumcision, they are expected to get married, although the community does not engage in traditional match-making as practised by, say, Kuria and Samburu. The dropouts who do not get marriage partners stay at home, and single-motherhood is currently on the rise despite the Kipsigis traditional abhorrence to children born out of wedlock. In addition, some poor families are unwilling to sell livestock, especially cattle, to educate their female children. The apparent preference for boys in paying school fees was due to the idea that women will eventually be married off to support other families, and that those who finish secondary school education tend to get married outside the location. 3.29. The primary schools are housed in poor semi-permanent structures with inadequate learning facilities (textbooks, stationery, equipment, etc). The proportion of primary school leavers that proceed to secondary school is low due to poverty (lack of fees), poor performance in national examinations, and early marriage for girls. The teachers reported that food stress occasioned by drought has made children weak, sleepy, and reduced concentration in the classroom. The pupil-teacher ratio, which stood at 40 in 1997, does not give teachers sufficient time to give personalized attention to students. In addition,
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household land parcels are getting smaller, and school enrolment has therefore been affected by the need for boys to take livestock for watering and across Amalo river for grazing. 3.30. A reportedly significant proportion of educated girls from the lower plains get married in upper Bomet or outside the district, thus reducing the availability of female teachers, which in turn means that school girls do not have role models. For example, there were 47 male primary school teachers and 4 females in 1997. Out of the four female teachers, only one was born in the location, while the rest have become residents through marriage. It is therefore not surprising that, out of about 50 primary school children who proceed to secondary school per year, only an estimated 20% are girls. 3.31. Out-migration of whole families outside the location and district has adversely affected the availability of teachers. In addition, the soil and climatic conditions in the lower zones (UM4 and UM5) are identical to the arid and semi-arid districts which are administratively considered hardship areas, and where civil servants and teachers are therefore given hardship allowances. Some parts of the lower zones should be considered hardship areas to increase retention of teachers and other civil servants. Secondary Education 3.32. Out of the 56 secondary schools in Bomet district, most are located in the upper plains in Sotik (14 schools), Bomet Central (12) and Konoin (8). Sigor division, with an estimated population of 65,000, has only three secondary schools. There is no secondary school in Lelaitich location, and students mostly enrol in Kaboson and Sigor while a smaller proportion go to Longisa, hence long distances to school. The exposure of students to communities outside their immediate environment has profound impact on their future outlook, which include girls searching for suitors outside the location (in the upper plains of Bomet and even Kericho district), which in turn affects parents’ willingness to send girls to secondary school or Standard Eight (lest they pass). Adult Education 3.33. Bomet district had 37 full-time and 74 part-time adult education teachers. Male enrolment in adult education is relatively small, not because they are literate, but because they loathe sitting with women (who may include their wives) and attendance is seen as admission of illiteracy. There are no sufficient resources, especially teachers, to start men-only classes. 3.34. Despite the heavy female workload due to socioeconomic environment (drawing water, household chores, farming, etc.) and the men’s attitude towards manual labour, women are still able to attend adult classes. The functional literacy curriculum includes the formation of women groups registered under the Ministry of Culture and Social Services. Some women groups have started to keep grade animals e.g. in Kimulot. 3.35. According to relevant Government officials, the obstacles to adult literacy include: (a) Lack of transport at the district and lower administrative levels for use by inspectors; (b) Lack of funds for exposure seminars and tours for teachers; (c) Non-promotion of teachers as the last promotions was for reference year 1979; (d) Insufficient publicity of the programme by the provincial administration; (e) Lack of premises for adult education officers at the district and lower administrative levels; and (f) Lack of office equipment e.g. typing machines. Girl-Child Issues and Concerns 3.36. In most patrilineal societies, boys tend to be valued more than girls. In Bomet, and more pronounced in Lelaitich, the desire for boys has had a profound impact on conjugal relations. In Western societies, sexual relations tend to correspond with the structure of marriage unions. However, in Lelaitich
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this is not always the case. If a woman bears about four girls in a row, the man may marry a second wife, and build a homestead for the first wife at the other end of the family holding. The estranged wife (barren or without sons) could ‘marry’ another woman who would proceed to bear their children by men who would have no obligation towards them or their children. The children would belong to the barren woman or ‘husband’ as she had paid bride price (Cotran, 1968). The name Chepkwony, meaning ‘of a woman’, traditionally signified that someone was a child of a marriage between two women5. 3.37. Wife inheritance is still practised. Those widows who refuse to be inherited (as human beings) are disinherited of their claims on family property. The apparent desire to punish male offsprings who may not obey their parents and the need to disinherit a woman who refuses to be inherited has resulted in lack of sub-division of land until the owner is too old or dead. As one person put, “I do not own land because my father has not died”. 3.38. Finally, female initiation has made the first seven years of primary education a gap-filler between childhood and initiation in preparation for marriage rites. Ironically, the religious sect opposed to providing AAK with child case histories has recorded some success in deemphasizing the cultural role of female circumcision and a change to more humane surgical procedures, and may be AAK’s main ally in influencing change in female initiation. Although the focus on education of girls is receiving due attention from community leaders, there is still need to sensitize parents and children on the need for education as a means to economic and social empowerment. HEALTH 3.39. As of 1996, there were 44 health facilities in the district comprising 35 dispensaries, 5 health centres, one sub-district hospital (in Konoin), and three hospitals (Kaplong, Tenwek and Longisa). Sigor division had only one health centre located near the division headquarters and three dispensaries. The 1995 outpatient morbidity statistics show that malaria had the highest incidence (35.3%) followed closely by respiratory tract infections (32.7%), skin diseases, intestinal worms, and diarrhoeal diseases. The significant incidence of intestinal worms and diarrhoeal diseases is attributable to poor water and sanitation, as well as the predisposition to half-cooked meat. 3.40. Infant mortality rates are fairly high. Infant mortality rates can be divided into neonatal and post-neonatal because deaths in the early part of infant life are governed mainly by prenatal influences (e.g. premature, congenital, malformation and delivery care), while deaths in the latter part of the first year are generally socioeconomic and environmental in origin (diseases and feeding). Data for 1995 from Kaplong hospital in Sotik showed a neonatal mortality rate of 2.3, while Tenwek Mission Hospital showed 6.5 per 100 live births. 3.41. The health and nutrition status of the district has improved after the district was carved out of Kericho. This has resulted in increase in vital services (schools, hospitals, roads) and the creation of more administrative units which has made it easier for the Government to closely monitor people’s living conditions. The lower zones experienced greater isolation when Bomet was a part of Kericho district. However, unreliable rainfall leads to seasonal food deficits in the lower zones. 3.42. Some major causes of malnutrition are early weaning and poor feeding practises. Among the Kipsigis, babies of only ten days old are given gruel by forced feeding (Blankhart, 1974). Fish and Fish (1995) also claim that the dietary habits of the traditional Kalenjin (specifically the Kipsigis) “were very close to those of the Mosaic laws given in the books of Leviticus and Deuteronomy”. For example, it was a taboo among the Kipsigis to eat pork (including the wild pig, forest hog, and tame pig) or rabbit. The pig industry is almost non-existent since it is ‘a dirt-feeding, excrement-eating animal’ (see Orchardson, 1961); popularity of eggs is hampered by beliefs that expectant mothers should not eat eggs; and that 5 See also, Monica Jesang Katam v Jackson Chepkwony & another [2011] eKLR.
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children should not eat certain parts of meat, say, liver and the brain. These beliefs are more pronounced in the lower plains. According to the Bomet MOH, protein-energy malnutrition is most prevalent in Sigor, Siongiroi, Chepalungu and some parts of Bomet Central and Longisa. 3.43. The community leaders in Lelaitich expressed concern about the impact of the increased consumption of traditional brew on health. Previously, the brew served a social function e.g. during initiation rites, but is slowly becoming a commercial venture. The expenditures related to initiation rites (brew, food, meat) are also exerting pressure on community resources, especially because it comes immediately before the beginning of New Year (November-December) when demand for school fees is highest.
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CHAPTER 4: SURVEY DESIGN AND IMPLEMENTATION
SAMPLE DESIGN AND SELECTION 4.1. The survey was carried out in the three sub-locations of Lelaitich location, namely, Lelaitich (total sample frame: 508 households), Kapsabul (528) and Lugumek (482). Based on 15% sampling fraction, the survey covered 225 households out of 1,518 households: Lelaitich (74 households), Kapsabul (79) and Lugumek (72). The administrative decisions that dictated the Lelaitich sample design include:
a) That the survey should include all villages in the location;
b) That the spatial unit of analysis would be the sub-location; 4.2. The total number of households included in the lists from the PRA was 1,518. Upon receipt of the lists, the first step was to organize the villages by sub-location and then assigning numbers to households beginning with 1 so that one sub-location became a stratum. The use of the term “strata” therefore refers to classification of households by sub-location. The second step was to select the total sample proportionate to the size of each stratum. The required sample was generated by use of systematic selection with a random start. Compared with random selection, systematic sampling has three advantages: (a) it is easier to draw; (b) it allows easy verification of the selection; and (c) if the list is in some order, the method provides a degree of stratification in respect to the variable on which the list is based (Macro International, 1996).
ESTIMATION PROCEDURES Blanks and Non-Response 4.3. There are various sources of errors/ bias in a sample survey or census. Errors could be introduced by misreporting, lack of data, enumerator or respondent bias, non-response, and in data processing. This section deals with non-response and its effects on sample weights. Unit non-response occurs when sampled subjects do not participate in the survey, while item non-response occurs when participants in the survey fail to provide answers to some of the questions. In a household survey, unit non-response could be introduced through refusals or failure to locate a household. Although it is difficult to rule out inclusion in the frame (N) of some households which did not exist or to exclude some which existed before the frame was constructed, i.e. out-of-scope, it was decided to treat the sample frame (N) as a true report of the number of households in December 1997. Therefore refusals and failure to locate were summed as non-response. 4.4. Filled survey and census questionnaires may contain blanks or missing values attributable to lack of data or a question that was not asked. Blanks and non-response splits the original population (N) into two subclasses: M non-blank members and B blanks and non-response, i.e. N=M+B. The presence of blanks and non-response introduces variation in the size of the sample, and may introduce errors in the final estimates if the responding and non-responding households have different socioeconomic characteristics. This variation is a function of the proportion M=M/N. However, the selection interval (k) and selection fraction (f) do not change since the blanks and non-response were identified after the original sample had been selected. 4.5. The sample frame used was created a year before the survey was conducted. As we shall see later, there was substantial out-migration of whole households during the intervening period. This implies that
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the sample non-response arising of out-migration should be treated differently from other types of non-response. However, the magnitude of other errors in the sample frame (e.g. in-migration if any, new households created through marriage, etc.) are not known. It was therefore decided to treat out-migration like any other type of non-response. Weighting 4.6. In the sample, each element had an equal chance of selection. Therefore each element has the weight of 1 in the sample total, and F=1/f in the population total, where f is the selection fraction. Since the sampling fraction in each stratum was equal to the sampling fraction for the universe, the procedure ensured a self-weighting sample6. 4.7. The basic weights, before adjustment for non-response, are the reciprocals of the probabilities of selection, i.e. w = m/n Where: w is the weight in the stratum;
m is the total number of households in the stratum; and
n is the sample size in the stratum 4.8. In producing survey estimates, the basic weights will be adjusted for non-response to arrive at final adjusted weight, which is the product of the basic weight and a non-response adjustment factor. The procedure of calculating the non-response (nr) factor for each stratum was as follows:
nr = n/i Where: nr = the non-response adjustment factor;
n = the total number of originally selected households;
i = the number of households which responded The adjusted weights are wa = w * nr = (m/n)*(n/i) = m/i, i.e. the total number of households divided by the number of households which responded.
AAK MEETING TO DISCUSS THE QUESTIONNAIRE 4.9. AAK organized a meeting of programme managers from the Western region to discuss the draft survey instruments (questionnaires and enumerators’ reference manual). Some of the suggested improvements of the draft instruments include: a. Survey estimates should be at sub-location and village level but no significance tests were to be
made for village-level estimates due to small sample sizes. b. Classification of households into poor/non-poor and male/female headed be done at analysis
stage (post-stratification) rather than be incorporated in sample design using PRA household listing. This is mainly because PRA measures relative poverty which is only relevant within the immediate environment in which the wealth ranking is conducted.
6. Rounding of the strata sample to the nearest integer introduces slight departures in the values of actual sampling fractions. However, this trivial departure is usually ignored (Kish, 1965).
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c. That data on school dropouts to include those that completed Primary 8 but did not continue to secondary school, and that the question would only be asked for those who dropped out during the period 1993-96.
d. That data on the main residential structure should include number of rooms, number of
windows, number of persons sleeping in it, and whether livestock sleep in there; and similar information be collected in cases where kitchen is separate from the main house.
e. Additions recommended in crop production schedules include (i) method of land preparation -
tractor, plough, hand-hoe, (ii) method of planting - broadcasting, line planting, (iii) access to extension services, (iv) use of fertilizer, and (v) type of storage - sacks, granary, etc.
f. That land holding section to pick information on households which have been allocated land by
their parents but no title deeds issued due to the apparent tendency for the people of the area to delay actual mutation and issuance of title deeds until they are very old.
PRE-TESTS 4.10. A two-day training of enumerators was conducted during 25-26 November 1997. The training was conducted using the draft questionnaires and enumerators’ reference manual. At the end of the training, the 12 enumerators formed four groups of three persons each to pre-test on each other. One person in the group acted as the respondent, the second as the enumerator, and the third took notes on the enumeration process. Each enumerator also conducted pre-tests on a household in the community, and a final debriefing meeting held to review the training phase of the survey. The pre-tests found inadequacies in the survey instruments especially on land tenure, which led to amendment of the draft questionnaire. The average interview time was two hours. There were no reports of respondent fatigue. It was therefore decided to retain the length of the questionnaire. 4.11. The training of enumerators and pre-tests led to a number of changes in the survey instruments. The changes include: a. The manual to emphasize the advantages of systematic sampling whether the households that
constitute the sample frame are ordered or not. The section on “Estimation Procedures” expound on the fact that those who respond and those who don’t may have different socioeconomic characteristics, hence the need to reduce non-response for the entire survey.
b. An insertion in the manual emphasising that the enumerator should “head-tune” the respondent
when starting to ask questions on a particular record type to ease communication with the respondent.
c. It was noted that the recorded age of children below one year would be misleading if the
reference date is taken to be the date of the interview since all households cannot be interviewed on the same day. To correct the problem, it was agreed that any child whose first birthday will be on or before 15 December 1997 will be recorded as “0” since this is the date the survey was expected to end.
d. The enumerators expressed reservations about respondents’ cooperation in answering questions
on sickness, but it was emphasised that it depends on how the enumerator introduces the purpose of the survey.
e. Children eligible for inclusion in Form B/S/L/2 are those whose recorded age in Form B/S/L/1
is 0-4 years since 4 completed years translates to a maximum of 59 completed months.
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f. It was emphasised that a TBA is recognized as such by the community. Other community personnel who assisted in delivery should be recorded under “other”. A child delivered in a health centre/ dispensary is expected to have been assisted by nurse/ midwife, while those born in hospitals should be recorded as having their delivery assisted by doctors whether a doctor or nurse assisted.
g. To minimize errors in recording quantities of food purchased, the enumerators were to ensure
that the total costs per food item are actual rather than imputed. To countercheck information on prices and quantities, a retail price survey was conducted alongside the household survey to determine the prevailing market prices to be used to convert food cost to weight for the purpose of estimating calorie supply by the use of food-to-energy conversion tables. The retail market survey entailed purchasing and weighing food items in representative markets in the location.
h. “Other meat” was likely to capture meat of wild game secured through hunting, and does not
therefore cost anything. It was agreed that the enumerators would indicate the animal whose meat is recorded and the weight in kilograms, but record total cost as “0”.
i. In the local context, the peak of the long rains is March-April and the short rains is August-
September. Therefore short rains will refer to August-September 1996, while the long rains will refer to March-April 1997. Consequently, the information on seasons was solicited on short rains first before covering long rains production.
j. Purchase of agricultural implements should be recorded once on the maize columns since the
implements are likely to be used for all crops. k. It was noted that quantity harvested may not balance with disposal due to postharvest losses e.g.
theft, and destruction by animals especially elephants (e.g. in Lugumek sub-location). If such situations arose during the survey, the enumerators were to note in the questionnaire.
l. On ownership of land, it was agreed that land purchased should be included under land owned
whether mutation and issuance of title deeds had been completed or not. However, land expected to be given by a parent under inheritance should be recorded as free access from parents rather than owned.
FIELDWORK 4.12. Field data collection started on 3rd December 1997. The advantage of the timing was that it was easy to bound annual recall for crop and livestock production, annual non-regular purchases, and income data. However, the survey coincided with the peak of cultural ceremonies and the 1997 election campaigns, which made the fieldwork extremely difficult for the enumerators and made it necessary to extend fieldwork to three weeks instead of the planned one week. 4.13. Household-level data on school dropouts is not supposed to be collected at the end of the year. Normally a dropout is taken to be somebody who was in school in the previous year but was not in school at the period of the survey. It was therefore not possible to analyze data on dropouts for reference year 1997. 4.14. The consultant checked the filled questionnaires with the enumerators on a continuous basis. In the first two days, some enumerators had to revisit respondents to clarify on some information collected, based on the outcome of the review of the questionnaires. However, by the third day, the enumerators had grasped all the conceptual issues and their application to the data collection exercise.
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4.15. The sample frame provided by AAK was fairly adequate except for a few cases. For example, a young boy sleeping alone apart from the family had been listed as an independent household. A decision was made to interview the whole household even though the whole household had not been selected. Another household was listed in two villages since it is close to the boundary of the villages, and could only be interviewed in the right village. 4.16. At the end of the fieldwork, AAK and the consultant held a debriefing meeting with the enumerators. Some of the issues raised concerned AAK and its activities in the area, mainly the community misgivings about taking case histories of their children for child sponsorship funding, and the fact that AAK has had little material impact on the ground outside of PRA work and the baseline survey undertaken by the community resource persons. However, the objection to case histories was only concentrated in one religious group. Some of the community elites were also aware that AAK has been involved in bridge and health centre projects within Bomet district but outside the DI. Although AAK’s involvement is mainly supervisory since the projects have been funded by the Japanese government, the community was not aware of the project details. 4.17. Some respondents were suspicious of the criteria used in the selection of households for the survey. The final sample, though randomly selected by the consultant without any prior knowledge of the socioeconomic characteristics of the respondents, included the chief and one assistant chief. Those who had refused to take part in child sponsorship thought they were included as a backdoor attempt to provide case histories through the questionnaire. An elderly lady refused to be interviewed on the suspicion that the survey was connected with opposition politics since the area lies within the “zone” of the ruling party KANU. 4.18. The enumerators stated that it was difficult to get very accurate responses on, say, date of birth. Some respondents were not sure of commodities they purchased and when, and the data may therefore have telescoping errors and recall loss. Some enumerators cited cases of slight underreporting of livestock owned, problems of memory recall with respect to chicken and eggs over a whole year, while underestimation of wage and self-employment income was widespread. The underestimation of wage income was more apparent where a wife reported income of her husband who was away. In Kipsirat village, a respondent was trying to exaggerate the household’s level of poverty in the hope of increasing the flow of resources from AAK to the community.
SUGGESTIONS FOR FUTURE IMPROVEMENTS IN SURVEY DESIGN 4.19. During fieldwork, some inadequacies of the survey instruments were apparent. Although most problems were rectified in the second and third day, it is important that they are corrected during survey design stage. One such problem related to the issue of woman-woman marriage, i.e. a woman marrying other women. The women and their spouses were recorded as married (monogamous, polygamous) and could end up separated, divorced or widowed, depending on the process of “unmarrying”. 4.20. At the end of survey, it was discovered that one enumerator took longer than scheduled to enumerate a household. Since the enumerator experienced some refusals, it is possible that this was caused by the long interview time. This could have been detected at an early stage if there was a control form for entering details on visits and revisits and the time it took to interview a particular household. 4.21. On illiteracy, subjective information was solicited on ability to read and write separately. This was intended to capture the household members who are on the margin of illiteracy, i.e. can read but cannot write. However, only three persons in the entire sample were picked at the illiteracy margin. It is possible that some enumerators did not solicit information on ability to read and write separately, although there is no evidence.
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4.22. In the case of membership to self-help groups, it became apparent that the Government has encouraged the formation of women and youth groups as a condition for eligibility to access funds raised through national harambees for both women and youth. The enumerators were instructed to note such groups in the questionnaires. The legends for types of self-help groups were later changed during data edit to separate the above-mentioned groups from other community self-help groups. In addition, community organizations without fixed membership, e.g. neighbourhood support with labour during cultivation, were excluded from the definition of groups. 4.23. On whether the mother had a child card, some enumerators were contented with the mother’s response without being shown the card. A small post-enumeration survey found that keeping of child cards was widespread partly due to community awareness arising from the efforts of Tenwek Mission Hospital health personnel. Enumeration errors on child immunization are therefore minimal. 4.24. The traditional residential structures have circular holes for ventilation, in addition to bigger windows. In Kapsabul sub-location one enumerator recorded the small holes as windows. It was not possible to revisit all the households to confirm the true position since the problem was discovered when the fieldwork was about halfway. 4.25. In two filled questionnaires an enumerator recorded chickens sleeping in the main house as livestock. However, the problem was sorted out in the field and the questionnaires corrected accordingly. 4.26. The fact that quantities of, say, maize, sorghum and millet sold are measured in 2-kg containers (goro-goro) led to initial confusion in Form B/S/L/4A of the questionnaire7. This was promptly addressed in the field. This is especially important in the estimation of calorie availability since the results depend on quantities rather than expenditures. In general, male respondents were less informed of household purchases compared with female respondents. 4.27. There is no electricity in the whole of the location, and it was not therefore necessary to put electricity in the questionnaire as an expenditure item. 4.28. The information solicited on food production and disposal was more appropriate for single-season crops. In the case of sweet potatoes where harvesting can span 3-4 years, acreage by season does not necessarily imply new planting. Enumerators also complained about switching from Shs to Kg in Form B/S/L/6B, and that quantity sold should have been collected in addition to the value of sales. This would have assisted the enumerators in balancing crop production with disposal. 4.29. On row 12, Form B/S/L/6B, the factors inhibiting crop production did not include “none”, and the enumerators were therefore required to record “none” if no inhibiting factor was reported by the respondent. The same process was applied on the problems inhibiting livestock production in Form B/S/L/7. Respondents found it difficult to remember livestock owned in December 1996, especially chicken; while milk sales should have included quantity in addition to value of sales. The latter would have assisted the enumerators in balancing milk production with disposal. 4.30. On land tenure, the survey questionnaire and enumerators’ reference manual implied that land accessed and not owned should only be solicited from those households which did not own land. However, cases where households both owned and accessed land they did not own were reported at the beginning of the survey. The problem was addressed in the field and enumerators instructed accordingly.
7 A goro-goro is the standard unit for buying and selling maize in Western Kenya. A goro-goro is a volume measure equivalent to roughly 2.25 kg of dry maize kernels.
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DATA ENTRY AND PROCESSING 4.31. One of the serious errors a survey could suffer from is loss of data. This may arise from loss of questionnaires, data storage equipment, or data outputs. To guard against such losses, the survey set up data control mechanisms. After the sample was selected, the names of the household heads were compiled by village and sub-location. A six-digit identification code was assigned against each household: the first digit represented the sub-location e.g. Lugumek (3); the next two digits represented the village e.g. Lugumek central (301, digit “3” for the sub-location and “01” for the first village); and three digits for the household number. 4.32. During training, enumerators were instructed that all questionnaires - completed, incomplete, spoilt and unused - should be returned at the completion of fieldwork. Upon receipt of the questionnaires, they were checked against the survey’s master control list, and the questionnaires were then filed by sub-location/ village to avoid losses or misplacement. 4.33. Data were entered into the computer using SPSS. The data entry programme included range rules (acceptable values for categories of variables e.g. 1, 2 for gender) and skip rules after a filter question (e.g. membership in self-help groups and whether one was sick in the two weeks prior to the survey). After completing data entry, the data entry clerks carried out data validation, which revealed some errors. In an effort to produce an error-free data file, it was decided to recheck all entries and correct all wrong entries. Some data, e.g. estimated number of households per village, were entered extraneously to allow computation of weights and estimation of total population. Tabulations were prepared using SPSS. Data on food relief was also entered at the analysis stage since the quantities given were evenly distributed by household throughout the location.
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CHAPTER 5: RESULTS OF THE FIELD SURVEY
RESPONSE RATES 5.1. The enumerators were instructed to classify the outcome of the survey interview as either completed; partial; vacant - housing unit not occupied; unable to contact on vacation, or unable to get an appointment (but household is “cooperative”, i.e. not refusing); refusal - household refused to be interviewed, household shows resistance after repeated attempts; unable to interview due to age, illness or impairment; unable to interview due to language; out-of-scope - dignitaries, foreigners intending to leave Kenya before survey ends, etc; and other (specify). In this report, response is defined to include “fully-completed” interview status, and all other interview outcomes were classified as non-response. 5.2. Table 9 shows that 225 households were covered, of which 197 were successfully interviewed, representing an 87.6% response rate. One partial interview whose data was discarded related to a household which was away during the month of November 1997, and no monthly expenditure data could therefore be collected. The vacant households comprise those who had migrated outside the district, mainly to neighbouring Nakuru (Olenguruone), Trans-Mara and Narok districts in the 12 months preceding the interview. The proportion of refusals (4.9%) is high for a rural survey. This mainly consists of households which had refused earlier AAK attempts to engage them in case-history for the child sponsorship funding, while others cited AAK’s delay in undertaking significant development activities in the DI. Fortunately, the baseline survey was conducted at the same time with the preliminary study on water supply to the location, which raised community hopes that AAK support was forthcoming. HOUSEHOLD AND DEMOGRAPHIC CHARACTERISTICS 5.3. Table 10 shows the distribution of the responding population by age and sex. The age structure of the population closely resembles the national structure as per the 1989 Population and Housing Census, with 49.2% below the age of 15 compared with the national average of 47.8%; while the population over 60 years was 5.3% compared with the national average of 4.8%. The sex ratio (males per 100 females) was 101.1 for Lelaitich sub-location, 108.3 in Kapsabul, and a high 128.1 in Lugumek, giving an overall average of 111.9. The sex ratio in Lugumek is high for the responding population below 24 years, while females exceed males for higher age groups. The estimated total population was 8,785, comprising 4,644 males and 4,141 females. 5.4. Table 12 shows the distribution of the responding population by sex and relation to household head. Most households were male-headed (78.7%), while Lelaitich (71.4%) and Lugumek (77.3%) were below the location average, compared with 86.8% in Kapsabul. Most of the household members (95.8%) were close relatives - father, mother, son, daughter, i.e. a high prevalence of nuclear families. Non-relatives were virtually non-existent. 5.4. Due to the youthful population, the distribution of the population by marital status shows that the majority were “never married” (68.2%). The conjugal relations show that there were 157 married males for 164 married females. The excess of females over males is largely explained by the woman-to-woman marriage unions, polygamy, and non-resident male heads. However, the man-woman and woman-woman unions were not distinguished during data entry. The final category comprises separated, divorced, widowed, as these were former unions that have “unmarried” through separation, divorce or death of spouse. There were more women who were reported as unmarried compared to men. This may be due to (a) the fact that it is more culturally acceptable for a man to remarry, which is also true of most communities in Kenya; and (b) polygamous unions where, say, a husband unmarries one wife would still remain married. 5.5. As shown in Table 14, the institution of marriage in the study area is universal, with all males and females having joined a marriage union by the age of 37 years, regardless of whether one unmarries
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thereafter. In addition, women marry younger than men as very few women reach the age of 24 without marrying. 5.6. Table 15 shows the distribution of the population attending school. About a third of the population was attending school at the end of 1997, with a higher proportion of males than females except in Kapsabul where the situation was reversed. Only a small proportion of the household members at school were in secondary school (4.8%), while the majority were in primary school (83.1%). The low secondary school enrolment is unlikely to be due to children learning away from home since the survey was conducted during school holidays. The primary school enrolment had a sex ratio of 126 males for 100 females. 5.7. The educational profile of those “not at school” shows that the majority had no education or had not gone beyond primary education. The number of women reported as both out-of-school and cannot read or write are almost the same; while there were more men reported as having no education but still reported themselves are literate. This may be due to the fact that men may have been exposed to environments that gave them elementary ability to read and write; or the males reported themselves as literate when they were not. This error cannot be avoided in a self-reporting literacy survey, unless one undertakes objective tests in reading and writing. This was, however, beyond the scope of this survey. 5.8. The age-grade mismatch is an important explanation of dropout rates. As shown in Table 18, there were more children in nursery school who were above the rational age of 6 completed years (63.0%) than those within the rational age (37.0%). In upper primary - Standards 5 to 8 - those above the rational age were more than those in the appropriate grades for the age group. Age-grade mismatch appears to affect both sexes. The age-grade mismatch is explained by late entry to school and repetition since the problem affects the entire education cycle. 5.9. Table 19 presents data on primary net and gross enrolment. The overall net enrolment ratio was 90.2%, with a high 94.1% in Kapsabul followed by Lelaitich (91.5%) and Lugumek (85.2%). The net enrolment ratio for females was higher than for males in Lelaitich and Kapsabul, but the ratios were reversed in the case of Lugumek. The high net enrolment ratio may be reflecting the situation as it was, although errors could be introduced by age misreporting. The gross enrolment ratios were above 100% except for females in Lugumek. The big difference between net and gross enrolment is attributed to age-grade mismatch. The gross primary school enrolment ratio for the location based on official enrolment data and estimated population (90.2%) was lower than that reported in the survey (110.1%). 5.10. The data on literacy shows that only three persons in the sample were reported as able to read but not able to write. In this survey, illiteracy was taken as inability to both read and write. Although the data is based on self-reporting rather than objective tests, the reported literacy level is higher than the national average. Lugumek (43.9%) reported slightly higher illiteracy rate than Lelaitich (42.3%) and Kapsabul (31.6%). The gap between male and female literacy rates was highest in Lelaitich (33.1 percentage points) and smallest in Kapsabul (18.1 percentage points). 5.11. A total of 84 children or 19.3% dropped out of school during 1993-96, with close to gender parity in dropout rates. However, the dropout rates in Kapsabul and Lugumek were almost double those reported in Lelaitich. The survey also solicited information on reasons for dropping out of school. In the case of boys, lack of fees was the main reason given (63.0%), and marriage for girls (50.0%). Out of the 38 girls reported to have dropped out of primary school, two were due to pregnancy and 19 due to marriage. However, the distinction between pregnancy and marriage is blurred since a girl who got pregnant and dropped out of school to marry is likely to have been reported under marriage rather than pregnancy. However, marriage as a reason for dropping out was more pronounced in Kapsabul and Lugumek than in Lelaitich, which supports the earlier finding that girls marry younger in the two sub-locations. 5.12. As shown in Table 22, most of the population (89.9%) was born within the location, with only
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2.6% born outside Bomet district. As expected, there were more women than men born outside the location, which may be attributed to marriage. However, it was not possible to collect information on those born in the location who might have later migrated outside the district. The only indicator of out-migration is the number of households which were listed in late 1996 but could not be interviewed one year later since they had moved out. However, discussions with community leaders revealed that out-migration of girls to upper Bomet and Kericho for the purpose of marriage is substantial. This shows that the community is not completely closed, although its contacts lean towards the neighbouring districts rather than upper Bomet. 5.13. The survey solicited information on household members’ membership of self-help groups. The self-help groups generally referred to as ‘Nyayo’ include groups which have been started as a condition for eligibility to national youth and women development funds. They are not yet operational, and were distinguished from the rest since they are not indigenous innovations and their performance can only be judged at a later date. As can be seen from Table 23, the most common membership in indigenous community groups was with respect to cash (merry-go-round) and assistance with labour. The data collected on assistance with labour refers to groups with fixed membership rather than general neighbourhood support also common in the area. Membership in cash groups included both men and women although male membership was not reported in Kapsabul. Membership in businesses (e.g. shops) was mostly reported in Lugumek, where more self-employment was also reported due to its proximity to Narok and neighbouring Kaboson. 5.14. As shown in Table 24, 148 household members (12.9%) had fallen sick during the two weeks preceding the interview. The main type of sickness for all age groups was cough/ cold (56.8%) followed by malaria/ fever (18.9%). When people fall sick, the most reported first action taken to restore health is purchase of over-the-counter (OTC) drugs (35.8%) followed by nothing/ traditional healer (33.8%) and visit to health facility (30.4%). This shows fairly low reliance on modern healthcare system and too much reliance on self-treatment or neglect of symptoms for serious illnesses e.g. malaria/ fever. However, it was not possible to determine the seriousness of the symptoms so as to gauge whether lack of visit to health facilities constitute serious laxity of personal health. 5.15. A disability is a limitation in an individual’s ability to perform an activity in a manner that is considered to be normal. Impairment is an abnormality in the structure or function of a part of the body or mind. Disabilities are caused by impairments, which are in turn caused by diseases, injuries or congenital (inborn) or peri-natal conditions. The six common disabilities are difficulties in speaking, hearing, seeing, moving legs (lower limbs) or arms (upper limbs), and learning (mental retardation), either in mild or profound form. The definition of disability excluded injuries or conditions of durations of less than six (6) months. 5.16. A census of disabled persons was conducted in conjunction with the 1989 Population and Housing Census in Kenya. In the census of disabled persons, data were recorded on disabilities rather than persons. Therefore, a person suffering from all six disabilities would be recorded 6 times, first as having difficulties in seeing, second as having difficulties in hearing, etc. A ratio of disability to the total population was to be interpreted as the prevalence of that disability. The census reported that the prevalence of disabilities in the total population was 1.4%, that most of the disabled persons had no education, and that the main disabilities were in the lower limbs, vision, hearing and mental retardation, as reported in the Economic Survey 1991. 5.17. The Lelaitich baseline survey reported a total of 24 disabilities or 2.08% of the total population. The most common disability was difficulties in the lower limbs (legs) which was higher for males than females; followed by difficulties in seeing (with gender parity); hearing (more reported among males); and arms (more reported among men). Although the data conforms with the national average reported in the 1989 Population and Housing Census, the sample is rather small to derive specific conclusions. As in the 1989 Census of Disabled Persons, the data showed higher levels of disability for males (2.46%) than females (1.65%).
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CHILD WELFARE 5.18. Form B/S/L/2 collected child particulars on place of delivery, the personnel who assisted in delivery, child immunization, and breastfeeding practices (including weaning foods). As shown in Table 26, most deliveries (73.0%) took place at home compared with a quarter delivered in a hospital/facility. Most deliveries were assisted by TBA/self (60.9%) followed by doctor (13.2%). This pattern was observed in Lelaitich and Kapsabul, but “nurse/midwife” was second in Lugumek. According to the enumerators’ reference manual, one would have expected that deliveries at hospital/ health facility would be assisted by a doctor or nurse/midwife. However, there were 5 cases of deliveries in health facilities where the women claimed that they were neglected, and were recorded as having assisted themselves in delivery. There was also a case of a home-delivery in Lugumek which was conducted at home by a qualified nurse on personal initiative. The data on place of delivery and the personnel who assisted in delivery did not match for all cases. 5.19. Although information on immunization was solicited for all children below five years, immunization coverage can only be computed for those who are supposed to have completed the immunization schedule, i.e. over 9 months. Normally, immunization coverage is computed for children of 11 completed months and over. The data shows high full immunization coverage (92.8%), which is roughly the same for both sexes. The dropout rate from one vaccine to the other in the immunization schedule is also minimal. Due to high immunization coverage, it was found unnecessary to cross-tabulate immunization status with, say, household incomes or education of the mother. 5.20. Information on breastfeeding is divided into two categories: those still breastfeeding and those that have stopped. This is because inclusion of those still breastfeeding tends to lower results on length of breastfeeding. The average number of months of exclusive breastfeeding (i.e. without any supplementation) was 4.0 months; and 18.2 months of any breastfeeding (with or without supplementation). The results are in line with the National Policy on Infant Feeding Practices which aims at encouraging mothers to exclusively breastfeed their babies for the first four months. In addition, 79.6% of the children are breastfed for over 12 months. The most common supplementation of mother’s milk was milk (other than breast) at 58.2% and porridge (35.7%). There was minimal supplementation with semi-solids. HOUSEHOLD AMENITIES 5.21. Form B/S/L/3 solicited information on construction materials of the main residential structure. Nearly all walls and floors were mud/ earth; while roofs were made of either grass (72.1%) or iron sheets (27.9%). There were no significant differences in construction materials by sub-location, although Kapsabul reported slightly higher incidence of iron sheet roofing. The analysis also includes combinations of wall, floor and roof. Out of the 194 mud walls (98.5% of the total), 142 were combined with grass roof and mud/earth floor; while the remaining 52 had iron sheet roofs, which are further split into 51 mud/earth and one cement floor. The three timber walls in the location have iron sheet roofing, while 2 have mud/ earth and one cement floor. Since the construction materials of the main residential structure are fairly similar in the location, it was not necessary to break them by household income or education of the household head. 5.22. The questionnaire solicited information on household ventilation (number of windows) and human-animal interaction in the kitchen or the main residential structure. The data shows that the main house had an average of 2.1 windows, and the results were fairly similar in the three sub-locations. In the main residential structure, human beings and livestock sleep in the same structure in 37.6% of the households. Only 69 (35.0%) of the households were reported as having a kitchen separate from the main residential structure, out of which human and livestock both sleep in 17 cases (24.6%). Humans and livestock both sleep in either the main house or kitchen in 95 households (48.2%).
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5.23. The main sources of water during the wet season were reported as pond/ dam and river, and mostly river during the dry season. The small proportion of houses with iron sheet roofing translates to little reliance on roof catchments as a source of water in the wet season. The average distance to water source was 0.79 km during the wet season and 3.07 km during the dry season. During the wet season, average distance to water source was lowest in Lelaitich (0.26 km), followed by Kapsabul (0.63 km) and Lugumek (1.45 km). In Lugumek, the distance to water source changes only slightly between the wet and dry seasons since Amalo river is the main source in both seasons. The distance to water sources in Lelaitich and Kapsabul during the wet season is made shorter in comparison with the dry season due to existence of ponds/ dams and roof catchments to a lesser extent. The household members mainly responsible for collecting water were reported as “wife and female children” in almost all cases. Water collected was reported as slightly over two 20-litre containers per day. A large proportion (90.9%) of the households does not do anything to the water before drinking. Although the survey collected data on price of water, only a small proportion of households responded since most households draw their own water. 5.24. The main method of disposal of human excreta was “bush” (55.3%), followed by own pit latrine (38.1%). The 13 households which reported as using neighbour’s pit latrine do not merit interpretation since they are likely to include those who use the bush but did not want to report so. Burning was the main form of rubbish disposal (83.2%). 5.25. All the households reported the main type of cooking fuel as firewood, while most households (97.0%) use paraffin as lighting fuel and the remaining 3.0% use firewood. The pattern was the same in the three sub-locations. 5.26. A reported 26.9% of the households had at least one bicycle, 41.6% had a working radio, and 38.1% had a plough. The ownership of bicycles, radios and ploughs was highest in Lugumek and lowest in Lelaitich and Kapsabul. According to the district agricultural staff, the use of ploughs is widespread, although the type and depth of top soils may demand hoe farming for preservation of soil fertility. However, ox-drawn ploughs may not be a threat to the thin top soil in the lower plains as tractor-drawn ploughs. 5.27. The average distance to local markets was reported as 3.44 km, with a high 4.08 km for Lelaitich and a low 2.40 km for Lugumek. However, a list of market places was not given in the manual, which may have introduced some errors. The average distance to primary school (1.34 km) was fairly uniform in the three sub-locations. The average distance to secondary school (7.42 km) was high since there is no secondary school in the whole location, and students are mostly enrolled in Kaboson and Sigor outside the location but within the division. The average distance to a health facility (3.97 km) is also high, which might explain the high reliance on lay-care healthcare system (over-the-counter drugs and “no action”) when one falls sick. AGRICULTURAL PRODUCTION Crop Production 5.28. On the basis of crop acreage shown in Table 41, the main crops grown in the location are maize and beans. The average maize acreage in the 1997 long rains season was 1.64 acres per household, with a high 2.58 acres in Lugumek and a low one acre in Kapsabul. The corresponding beans acreage was 0.44 acres, with a high 0.49 acres in Lelaitich and a low 0.36 acres in Kapsabul. The planting for 1996 short rains was minimal, and almost all crops failed throughout the location. The growing of millet, a crop which is important in the traditional Kipsigis culture and cultural rites, has virtually disappeared, and sorghum growing is almost non-existent. The average figures in Tables 41 and 42 are per responding household and not necessarily those which had planted the crops. 5.29. The purchase of certified maize seed formed the bulk of avoidable costs in crop production
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(52.5%), followed by hired labour for land preparation (24.6%). This pattern was reported in the three sub-locations. The use of fertilizer for any of the listed crops was negligible. 5.30. The productivity as measured by quantity harvested per acre was low. In the short rains, the average kgs of maize harvested per acre was 126.6, with 65.0 kg in Lelaitich sub-location, 173.6 kg in Kapsabul and 285.0 kg in Lugumek. In the long rains, the average kgs of maize harvested per acre was 182.2 kg, with 127.8 kg in Lelaitich sub-location, 180.3 kg in Kapsabul and 209.7 kg in Lugumek. The average maize harvest per household for the long rains was 300 kg, with about two 90-kg bags in Lelaitich and Kapsabul and 6 bags in Lugumek. Most of the maize harvest was consumed in the household. The highest consumption of maize harvest was in Lelaitich (82.6%) and Kapsabul (74.8%), while Lugumek consumed 38.6% and had 40.9% in store. Maize sales were higher in Lugumek (about one 90-kg bag per household) than in the other two sub-locations. The pressure or temptation to sell maize in Lugumek can be explained by their better harvest and their close proximity to Narok where there has been thriving trade between the Kipsigis and the Maasai. As we shall see later, Lugumek has more self-employment opportunities due to their closeness to both Narok district and Kaboson. The viability of the current types of crops grown in the location is in doubt, given the low output per acre and hidden costs in the form of unpaid family labour. 5.31. Total harvest for both short and long rains was estimated at 535 tons of maize, millet (5 tons), sorghum (4 tons), beans (9 tons) and sweet potatoes (36 tons). Lugumek sub-location accounted for 52% of maize and 74% of millet production; Kapsabul did not have any harvest of millet and sorghum; while production of sweet potatoes in Lugumek is negligible. 5.32. Table 43 shows the household members mainly responsible for various tasks related to crop production, namely, land preparation, planting, weeding and harvesting. Responses for long-rains maize and beans are the only ones analyzed since acreage for the other crops were minimal. In the three sub-locations, husbands and male children were mainly responsible for land preparation, while wives and female children were mainly responsible for weeding and harvesting. In Lelaitich, wives and female children were mainly responsible for planting maize and beans; while husbands and male children were mainly responsible for planting maize and beans in Kapsabul and Lugumek. The use of hired labour was minimal and was mainly in land preparation. 5.33. The main method of land preparation was digging/ploughing (97.6%) of the households which responded to the question. The implements for land preparation were plough (79.5%), tractor (12.7%) and hand-hoe (7.8%). The main method of planting maize was line-planting (92.8%) and broadcasting (7.2%). Livestock Production 5.34. Each household in the location had an average of 5.46 cattle, 3.57 goats, 1.26 sheep, 9.81 chickens and 0.73 donkeys in December 1997. The stocks were only a marginal improvement over the December 1996 figures. The average stocks per household were highest in Lugumek followed by Kapsabul, while Lelaitich reported the lowest averages. There were no pure breed grade cattle in the whole sample. As shown in Table 44, the livestock population for reference period December 1997 was estimated at 7,945 cattle (with Lugumek accounting for 43.7%), 5,158 goats (Lugumek: 51.7%), 1,878 sheep, 15,544 chickens and 1,095 donkeys. Honey production and keeping of “other poultry” e.g. ducks was rare, and the results do not therefore merit interpretation. 5.35. Livestock mortality is high, especially for chicken. Chicken mortality during 1997 was 39.6% of the mean number of live chickens in December 1996 and 1997, followed by sheep (18.2%), cattle (13.6%), goats (8.6%) and donkeys (3.0%). Chicken mortality was highest in Lugumek (51.7%) mainly due to high incidence of a variety of diseases. However, mortality rates for cattle and sheep were highest in Lelaitich at 16.4% and 31.2%, respectively, while that of goats was highest in Lugumek (11.4%). Generally, livestock mortality was lowest in Kapsabul.
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5.36. Income from sale of cattle was highest in Kapsabul and Lugumek, and lowest in Lelaitich. Sale of chicken was highest in Lugumek, followed by Lelaitich, and was lowest in Kapsabul. Milk production was estimated at about a litre per day per household; sheep are not milked; and only some limited milking of goats was reported in Lelaitich and Kapsabul. Although the survey reported 9.81 chickens per household, this only translated to 0.66 eggs per day. Lelaitich location is a net recipient of livestock gifts in the form of cattle and goats and net givers of chickens and donkeys. 5.37. Table 45 shows the livestock costs incurred per household. The major cost item was dipping (35.2%), although it was rather low in Kapsabul (16.2%). The only operational cattle dip is in Lelaitich sub-location, hence the low dipping costs reported in Kapsabul. This was followed by vaccination/drugs/veterinary services (29.9%). Dipping accounted for the largest share of animal production costs in Lelaitich (42.5%) and Lugumek (42.4%), while vaccination/drugs/veterinary services (37.5%) and hired labour (37.0%) were the highest in Kapsabul. Purchase of commercial feeds and mineral supplement took 30.5% of livestock costs in Lelaitich, and minimal proportions in Kapsabul and Lugumek. The use of hired labour to look after livestock was highest in Kapsabul. SOURCES OF HOUSEHOLD INCOME 5.38. The main sources of livelihoods were crops, livestock, wage and self employment, and food relief. Income from agricultural sources (crops and livestock) include own consumption and sale of crop produce, livestock and livestock products. The costs deducted only included direct costs and does not include the imputed costs of unpaid family labour. Total income is the total agricultural income; income from employment (wages and pensions), self-employment, lease/ rental income, and net transfers (cash and in-kind gifts received less gifts given out). The value of food relief during the year, which is equivalent to about Shs 2,000 per household, was not included. 5.39. As can be seen from Table 46, the main source of household income was paid employment (42.9%), followed by livestock income (25.6%), crop income (16.4%) and self-employment income (14.7%). The contribution of paid employment income to total income was highest in Kapsabul (50.3%) and lowest in Lugumek (34.7%). The contribution of self-employment was highest in Lelaitich and lowest in Kapsabul, although more household members were reported as being in self-employment in Lugumek than in the other two sub-locations. Crop income was highest in Lugumek, while the contributions of livestock income were around 25% in the three sub-locations. Overall, the highest average household income was reported in Lugumek and lowest in Lelaitich. The location was a net recipient of income transfers (excluding food relief, and crop and livestock transfers). 5.40. Table 48 shows household income by sex of household head. Overall, the average household income in female-headed households was less than a third of the income of male-headed households. Female-headed households had negligible contribution of wage income to total income in the three sub-locations. The main sources of income for male-headed households were wage income (46.6%) and agricultural income (39.0%); while the main sources for female-headed households were agricultural income (76.0%) and self-employment income (21.1%). 5.41. Table 49 shows a strong association between household income and education of the household head. For the whole location, average household income for heads who had attended secondary education, regardless of whether they completed, was almost three times the income of those with either none or nursery education, while those with some primary education are marginally better than those with no education. However, the contribution of wage income to total income increases with the level of education of the household head in the three sub-locations. In Lelaitich sub-location, the wage income of those with secondary education was 17 times that of those with no education, 14 times in Kapsabul, and 5 times in Lugumek. Generally, the shares of both crop and livestock incomes decrease as educational attainment increases. Households whose heads had no education were net recipients of transfers, while those with secondary education were net givers.
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5.42. Table 50 shows the relationship between household income and age of household head. Overall, in the three sub-locations, household income was lowest for the age group 20-35 years, highest for age-group 35-50, and then declined thereafter. The share of wage income declines with age, except in Kapsabul where the contribution of wage income was highest for age group 35-50 years. In the three sub-locations, the share of livestock income was highest for households whose heads were over 50 years. Households with young household heads were net givers, while households with older heads were net recipients of transfers. 5.43. Income per capita data may lead to different conclusions since it factors in household size. For example, per capita income by sex of household head paints a less unequal picture due to the fact that female-headed households were smaller than male-headed households in the three sub-locations. Likewise, household size generally increase with education of household head; while it was highest for age-group 35-50 compared with younger or older age-groups. 5.44. Out of 52 household members who had paid employment income, 18 (34.6%) were from Kapsabul, while Lelaitich and Lugumek had 17 each (32.7%). However, self-employment was not evenly distributed in the location. Out of 72 reported self-employment activities, 48 (66.7%) were in Lugumek, 16 (22.2%) in Lelaitich, and 8 (11.1%) in Kapsabul. LAND OWNERSHIP AND ACCESS 5.45. Form B/S/L/8 also solicited information on land tenure. The average holding owned within the district was 4.30 acres, with a high 5.24 acres in Lugumek, followed by Lelaitich (3.86 acres) and Kapsabul (3.79 acres). The average land owned outside the district was 0.61 acres, with 1.13 acres for households in Lugumek, 0.66 acres in Kapsabul, and none in Lelaitich. The average land owned was therefore 4.91 acres per household, the highest being Lugumek (6.37 acres), followed by Kapsabul (4.45 acres) and Lelaitich (3.86 acres). 5.46. According to community members, parents do not normally subdivide their land until they are very old; or fail to do formal mutation and survey. The survey obtained information on land accessed for household use but was not owned. As shown in Table 51, the average land accessed from parents but not owned was 1.64 acres (97.6% of total land accessed but not owned). This phenomenon is common throughout the location. In some instances, even married grandchildren could not own land since their fathers had no land registered in their names. The land tenure problems could be a source of strain in the community. 5.47. Female-headed households had higher acreage of land owned than male-headed households. Female-headed households accessed less additional land, all of which was from parents. Generally, those with no education owned more land (8.01 acres), followed by secondary education (6.07 acres) and primary education (1.43 acres). However, those with primary and secondary education accessed more land that they did not own compared to those without education. Land owned increases with age of household head, while land accessed and not owned decreases with age of household head. HOUSEHOLD CONSUMPTION PATTERNS 5.48. Rent data for residential premises was not collected since it was considered insignificant in a rural setting. Food relief was included in consumption but not in income. Consumption includes purchases, and own-consumption from crops and livestock and livestock products. The expenditure item “meals eaten out” was not analyzed separately since it was negligible, as eating food in one’s house has the significance of a covenant within the Kipsigis culture. 5.49. According to Table 58, monthly household consumption was estimated at Shs 3,715; the highest being Kapsabul (Shs 4,321), followed by Lugumek (Shs 3,405) and Lelaitich (Shs 3,384). Food
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consumption accounted for 72.9% of total consumption and non-food 27.1%, which is consistent with rural settings. Total consumption comprises 51.6% food purchases, 27.1% non-food purchases, and 21.3% own-consumption. The high proportion of food purchases (which includes food relief) is an indicator of vulnerability to outside markets. 5.50. Total consumption in male-headed households was Shs 3,988 compared with Shs 2,706 in female-headed households, which is consistent with gender disparities in incomes reported above. The share of food (purchases and own consumption) in total consumption is higher for households with female heads, which is also consistent with Engel’s law of declining food share as income rises. Alcohol consumption was highest in Lelaitich (4.8%), followed by Kapsabul (2.7%) and Lugumek (1.1%); while male-headed households spent more on alcohol (3.0%) compared with female-headed households (1.8%). Overall, education (6.5%) was the highest non-food expenditure, followed by household operations (3.6%), health (3.5%) and clothing (3.5%). 5.51. Table 60 shows that total consumption per capita was Shs 749, with the highest reported in Kapsabul (Shs 839) followed by Lugumek (Shs 714) and Lelaitich (Shs 689). There was a rank reversal in disparity of per capita income by sex of household head compared to total household income since households with female heads were on average smaller than those with male heads. 5.52. Total household size was converted to adult equivalents using 0-3 years as 0.4 adult equivalent, 4-7 years as 0.65, 8-12 as 0.8, and 13 and over as 1.0, based on food consumption tables published on behalf of the Kenya Government (Sehmi, 1993; see also Platt, 1962). The estimated calorie availability was 2,383 kilocalories per adult equivalent per day, with the highest in Kapsabul (2,668), followed by Lelaitich (2,318) and Lugumek (2,151). Female-headed households had higher adult equivalent calorie supply (2,909) compared with male-headed households (2,240), mainly due to the structure of consumption and effects of the relatively smaller household sizes. The main source of calorie supply were cereals (74.5%) followed by milk/ eggs (10.9%). Since the recommended daily allowance (RDA) is 2,600 kilo-calories, the data show mean food energy deficits except in Kapsabul. Overall, 62.4% of the households were below the RDA, with a low 48.5% in Kapsabul, followed by Lelaitich (65.1%) and Lugumek (74.2%). 5.53. The mean protein availability was 96 units, with the highest in Kapsabul (105), followed by Lelaitich (96) and Lugumek (87). Protein supply was higher in female-headed households (116) compared to male-headed households (91). The main sources of protein were cereals (69.1%) followed by milk/ eggs (15.6%). The recommended daily allowance is 49 units. The excess protein units above the RDA may be spurious since the major source of proteins is cereals, which tends to have less digestibility than animal proteins and pulses. 5.54. However, the use of fixed food weight-to-calorie conversion factors for the whole location and over the entire income profile might be inappropriate due to changing food quality and food preparation methods. As income rises, rich families are likely to consume more expensive calories (Behrman and Deolalikar, 1987; Bouis, 1992; Bouis, 1994). Distribution of welfare using calorie intake will concomitantly appear more egalitarian than that derived using food expenditures. In line with the United Nations National Household Survey Capability Programme, a household is deemed poor if, prudently managing its budget, cannot even meet its nutritional requirements. Some families or individuals may report food calorie deficit due to high consumption of non-food items. While these families will be counted as food poor, they will be counted as non-poor when total expenditure data is used to identify and determine the extent of poverty. In addition, household budget survey data does not normally specify whether quantities consumed were fresh or dry, which makes it difficult to apply the correct conversion factors. 5.55. Household calorie availability also need to be adjusted for leakages due to plate waste, loss in cooking and other food preparation, feeding of animals, and feeding non-household members such as guests, hired farm labourers, and servants. Nutrient intake is affected by other variables e.g. non-nutrient
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food attributes (freshness of food products purchased, their cleanliness, their storability or shelf-life, and so forth), privately-provided inputs (time and care to prepare food, including cleaning, cooking, boiling water, and refrigeration which ensures that food does not get contaminated or spoilt), publicly-provided inputs (sewerage, water, electricity, and nutritional information), and health status (e.g. gut parasites) which can influence the degree of absorption of nutrients.
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CHAPTER 6: OVERVIEW, FINDINGS AND RECOMMENDATIONS
OVERVIEW 6.1. The PRA conducted in November 1996 brought up the following as the key priority issues that contribute to poverty in Lelaitich: (a) Long distances to permanent water sources; and contaminated water; (b) Poor educational standards due to poor learning facilities, caused by low incomes and poor parental attitudes to education especially that of girls; and lack of tertiary education institutions; (c) Food insecurity aggravated by lack of alternative livelihoods sources except rain-fed agriculture, and limited knowledge on the best crop production methods due to inadequate extension services; and (d) Poor communication e.g. road network that leads to isolation of the location; 6.2. This report of the Lelaitich baseline survey carried out in December 1997 gives the socioeconomic characteristics of Bomet in general and Lelaitich in particular, and the results of the field survey. As in the 1996 PRA, the community identified the major problems as food security, quality of water and distance to water points for both man and livestock, poor attitude towards education (especially of girls), poor road network, poor community organization, and distance to firewood (which is mostly collected in Narok across the Amalo river). Despite the severe shortage of firewood, there is only one tree nursery (managed by Government) near Amalo river which did not sell any trees in 1997 since it is rain-fed. On infrastructure, the community noted that Sigor-Lelaitich road is passable during the rainy season (although the bridge across Cheptare river is weak and a danger to both the community and AAK staff); Mulot-Lelaitich road is impassable; while the Lelaitich side of Lelaitich-Chebunyo road is also impassable. There was also no bridge to cross the Amalo river, which is a threat to both people and livestock due to the need to graze livestock, collect firewood, and cultivate rented land parcels in Narok. For Bomet district as a whole, completion of the Nairobi-Narok-Bomet road would reduce distance by 130 km compared to the Nairobi-Kericho-Bomet road.
ACCURACY OF SURVEY RESULTS 6.3. In this survey, a maximum of three visits were made to each selected household so as to enhance response. Although there were some refusals, discussions with enumerators revealed that the non-responding households did not have different socioeconomic characteristics from those who responded. However, one expects the survey to suffer from recall loss (forgetting an event that occurred during the reference period) and telescoping errors (forgetting when an event occurred) especially annual expenditure, income and production. 6.4. In addition to sampling errors, the survey results may have been compromised by any of the following non-sampling errors: (a) Inaccuracies in the sample frame e.g. omissions during the initial household listings, households that had moved out of the location, and new households that might have come up through marriage and in-migration. (b) Inaccuracy of information provided by the respondents;
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(c) Errors by interviewer in recording responses; or (d) Errors in editing, coding, and data entry. 6.5. Although little could be done about (a) and (b), the other errors were minimized by close supervision of the data collection exercise, editing of survey returns, and thorough checking of data entry. The cooperation of both respondents and enumerators is likely to have improved the overall success and accuracy of the survey. For example, the age profile of the population was largely similar to that of the old Kericho as reported in the 1989 census. 6.6 At the end of the enumeration exercise, enumerators reported that some respondents felt that their involvement in the survey helped them to understand the household and farm-level economy better. Enumerators also reported learning from their involvement in the survey. This is likely to assist AAK in future action-research activities in the area. SUMMARY OF THE MAIN FINDINGS Household and Demographic Characteristics 6.7. Parents mainly send their children to pre-school because it is a pre-requisite for admission to primary school. This was evident from the fact that most of the children attend for one year or less. The main problems facing pre-school education are poor and irregular remuneration of teachers, non-payment of fees, lack of support by parents due to ignorance about the pivotal role of early childhood education on long-term child development, and long distance to pre-school centres. 6.8. Another concern was with respect to enrolment, dropout and pass rates in primary education, which lead to low enrolment in secondary school. The primary schools are made of poor semi-permanent structures with inadequate learning facilities (textbooks, stationery and equipment). The proportion of primary school leavers that proceed to secondary school is low due to poverty (lack of fees), poor performance in national examinations, and early marriage for girls. There is no secondary school in the location, which translates to long distances to school. 6.9. Female circumcision appears to be a cultural convenience since it offloads parental obligations towards the girl-child. There may be need to sensitize the community on benefits of female education, joining school at the right age, and postponement of circumcision until after completion of primary education. 6.10. With respect to community organization, people are generally supportive of each other; there were women groups in posho mills, poultry-keeping, etc; but generally the traditional mutual support that Kipsigis are known for has not been converted to larger community institutions. Previous initiatives have been the support in constructing water tanks mainly in primary schools by the Catholic Church; the training of community-based health resource persons by Tenwek Mission Hospital; while Government initiatives have been in paying primary school teachers and the recent food relief. There are therefore limited examples of local community-based institutions and people’s participation in community projects that AAK can draw upon. Child Welfare 6.11. The reported immunization coverage was high, partly due to community sensitization by Tenwek Mission Hospital. AAK can supplement community and the other NGOs in equipping static health facilities to reduce walking distances. The mothers understand the need to breastfeed for a long time and the type of supplementation required.
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Household Amenities 6.12. The predominant type of main residential structure was made of earth floor and wall with grass thatching regardless of income or the level of education. The residential structures fit the description of a European traveller to Kipsigis country at the turn of the century. Mr Hotchkiss, who later acquired a farm in the Kipsigis country, wrote: “The sight that greeted us was magnificent and pathetic. A wonderful country of rolling hills and tumbling streams confronted us, a country capable of supporting a great population. Yet what we found was a nearly barren landscape with miserable toadstool [i.e. umbrella-shaped] huts scattered over the face of it” (cited in Mwanzi, 1977). At the apex of the roof is a wooden post sticking up like a lightning rod, which represents the man of the house and is therefore removed upon his death, but his wife and young children may continue to occupy the hut. 6.13. In about half of the households, people slept in the same houses with livestock (excluding chicken). The sources of water are mainly salty, polluted rivers, and ponds/ dams that are even sources of worms that infect livestock; while distances to water points are also long. Although the questionnaire did not solicit information on distance to firewood, some households reported that they travel further to collect firewood than to draw water. AAK’s water programme therefore needs to support the Government tree nursery for reforestation, which would ultimately increase firewood and wood for fencing. 6.14. Most households reported that they do not do anything to water before drinking. In addition, the use of toilets is not widespread, partly due to ignorance; and partly due to soils and rock formation. Some areas e.g. Koita (meaning a ‘stone’) are rocky, while the soils in most of the location do not allow percolation, and toilets consequently overflow during the rainy season, threatening the environment. Those without toilets reported that the problems were rock formation, collapsing pit walls, and lack of/limited water percolation in the wet season. However, the incidence of sanitation-related diseases (e.g. cholera) is low in the whole of Bomet district despite poor environmental sanitation. Agricultural Production 6.15. The main crops grown are maize and beans in the long season. The location has virtually stopped growing traditional crops (millet and sorghum). Millet production is almost non-existent due to fungoid diseases, is tedious in terms of its labour requirements, and likes plenty of potash (which can only be obtained from fertilizers). The viability of the current crops grown is in doubt, given the low productivity and the hidden costs in the form of unpaid family labour. In addition, the widespread use of ploughs in land preparation also poses danger to long-term soil fertility. The current crop mix is not economical for the area, and there is need to experiment with, say, oranges and sunflower, if marketing channels are improved. 6.16. The main types of livestock are zebu cattle, goats and chicken. However, livestock mortality is fairly high, especially for chickens. This is mainly attributed to worms from ponds/ dams, low rate of dipping, limited expenditure on drugs and vaccination, and inadequate agricultural extension. In general, livestock production is a more viable source of livelihoods than the crops currently grown. Sources of Household Income 6.17. The main source of income is paid employment, followed by livestock and crops. Self-employment was minimal except in Lugumek. Overall, male-headed households reported higher household income than female-headed households, although the average household size was smaller in the latter. There was also strong association between household income and education of the household head.
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Land Ownership and Access 6.18. According to community members, parents do not normally subdivide their land until they are very old. The data showed that land owned increases with age, while land accessed decreases with age. In some instances, even married grandchildren could not own land since their fathers had no land registered in their names. The land tenure problems could be a source of strain in the community. ACTIVITIES UNDERTAKEN TO-DATE Activities in the District under the SDD programme 6.19. The DI managed to support two (2) health projects (Koiywa and Ainamoi hospitals) by providing basic equipment, although there was inadequate support from the relevant Government ministry. Following AAK’s proposal to the Embassy of Japan for $ 35,676, the community was jointly mobilized by AAK and Ministry of Health (MOH) staff in preparation for equipping Koiywa health centre. Equipment worth Shs 2.3 million was supplied and delivered to the hospital and those for outpatient services are already in use. Maternal child health (MCH) services have been initiated and child immunization started in June 1997; while community-based healthcare activities through education of communities at the facility have been intensified. Maternity services are expected to commence by the end of 1997 after the repair of the underground water tank. The Government has posted four additional staff (clinical officer, a registered community nurse, an enrolled community nurse and a patient attendant). 6.20. One of the biggest achievements is the community participation and ownership of both men and women as demonstrated by their willingness to attend to relevant meetings and commitment to spend time and resources to ensure success of the project. Training workshops facilitated by MOH have been held with hospital management and the committees on day-to-day management and the role of the committee during and after project implementation. However, the community contribution towards construction of staff houses and a water tank has not been sufficient ostensibly because of the current food stress, and Koiywa hospital has not therefore been able to offer inpatient services which require residential staff and adequate water. 6.21. A proposal similar to that of Koiywa was submitted to Embassy of Japan for $ 35,676 for the implementation of Ainamoi sub-district hospital. The hospital received two more staffs in June 1997, while equipment worth Shs 2.3 million has been delivered to the facility. A management committee of 13 persons is in place and received a two-day informal training on hospital management. The facility is not yet in use. 6.22. AAK also received $ 35,871 (about Shs 2.02 million) from the Government of Japan for the construction of Kiptui foot-bridge on Itare river, approximately 5 kilometres from Litein town in Bomet district. The community had been using a makeshift bridge made of timber which costs 5-8 lives annually. A number of animals especially donkeys also drown when ferrying goods across the river during the rainy season when the river floods. The steel bridge, once completed, shall ease transportation of goods and people between Kimulot and Buret divisions. Core Activities in the DI Area 6.23. In 1997, the DI recruited core staff, namely, Assistant Programme Coordinator (APC) and Community Development Worker (CDW). The DI enlisted 12 community resource persons (CORPs) who received three-week training on induction and sponsorship management. Through the use of the CORPs and the community institutions, the DI collected 1,500 case histories for UK marketing. Other logistical activities include the establishment of three sub-location committees which were key in case-history collection, and the establishment of the DI office at Bomet district headquarters and a field office at Kinyang’a.
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6.24. On community organisation, the DI has focused on mobilisation and capacity building of the communities through the traditional and upcoming institutions to plan, manage and implement their own activities. The DI has initiated the formation of sub-location and some village institutions. On recognition of the crucial role played by other actors in development, the DI initiated a District NGO forum which is in the process of developing its constitution and guidelines for the current NGOs working in the district. There have been discussions on the priority issues in education, their root causes and possible solutions, especially with reference to early childhood and primary school education. AAK has involved all key actors in its planning and implementation, including the 1998 Plan & Budgets. The DI has also played an active role in the District Development Committee (DDC). 6.25. The 1998 Plan focuses on community organisation with the village development committee (VDC) as the centre point for community development. The DI will hence focus its attention in building the capacities of community institutions in order to enable them to manage their development programmes. These institutions will be expected to mobilize the community at the grassroots so as to ultimately build their capacity to design, plan, implement and manage their own development. AAK will lay emphasis on raising awareness on the importance of education aimed at raising school retention rates and mean scores, particularly of the girl-child, through sensitization of parents, pupils, school committees, VDCs, and education officials. The water programme will revolve around planning and implementing the most viable water sources for the community. However, the expected coverage will be established after project design. Activities designed to improve livelihoods will revolve around building management and financial skills of traditional women groups in Lelaitich. The skills improvements are ultimately aimed at enhancing management skills in income generating activities (IGAs) and hence raise family income. The DI will attempt to strengthen the newly-formed District NGO network with the aim of influencing the general concerns of tackling poverty. The DI also intends to influence other actors in Bomet District into focusing on the poorest communities. 6.26. The staff of the DI includes a Programme Coordinator (PC), Assistant Programme Coordinator (APC) and Community Development Worker (CDW). The PC is currently stationed at Bomet. The PC is expected to move to Sigor division headquarters soon as there are no telephone and electricity services in the project area (Lelaitich). 6.27. AAK staff will face two major challenges. First, the APC and CDW were recently recruited to AAK, and there might be a case for posting them to the older AAK development areas (DAs) for, say, six months to familiarize themselves with AAK operations. Secondly, in the older DAs, there were staff specialized in, say, water technologies, food security and health. In the new DIs where staff strength will be minimal, AAK has to develop models of cooperation with other partners (e.g. Government, private sector, NGOs) to ensure quality service delivery and furtherance of AAK’s mission with respect to empowerment and increased ability of the poor to negotiate their own future. 6.28. AAK has grouped its DAs and DIs into Eastern, Northern, Western and Coast clusters. Each cluster has a regional coordinator and a regional accountant. The DAs and DIs in a cluster are expected to be mutually supportive, which was evident in the review of survey instruments for Busia and Bomet baseline surveys. However, there is need for close coordination between a cluster and other clusters and AAK headquarters. Without such collaboration, an understaffed DI might succumb to Diversionary Interests (DI) of cooperating partners in the project area and those of the cluster in which it is nested. RECOMMENDATIONS 6.29. AAK, together with other actors (Government, NGOs and community) should focus on critical areas necessary to improve the socioeconomic status of the DI population. Based on the findings of the household survey and discussions with local leaders, some of the areas that need to be addressed are:
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(a) Encourage other actors to participate in the improvement of the road network and bridges (across Cheptare river and two bridges across Amalo river - near Kinyang’a and at the boundary with Kaboson).
(b) Influence Government to increase the flow of resources to Lelaitich and the lower plains,
including infrastructure development, agricultural research and extension services, etc. (c) AAK should assist the office of the District Development Officer, Bomet, to prepare
socioeconomic profiles of all areas in Bomet, so as to give a more representative picture of the living conditions.
(d) Support Government efforts in afforestation in Lelaitich. (e) Work with Government and the communities on developing models of farming practices in the
lower plains, and agricultural extension geared towards crop diversification. (f) Sensitize the community on the need for proper animal husbandry (dipping, vaccination, salt
supplementation), including the need for community and/or private investment in veterinary drug stores.
(g) Encourage the community to keep poultry, consume chicken and eggs, and improve extension
services in light of the high chicken mortality. (h) Implement the planned activities in provision of water as a priority. (i) Support the equipping of static health facilities so as to reduce travel distances, and thus reduce
reliance on lay-care health restoration. (j) Focus on improving the structures that house pre-schools, and training of pre-school teachers. (k) Support the development of primary school education through improvement of physical
facilities, and the training of school management committees. (l) Improve girl-child education through joining school at the right age, delay of initiation until after
completion of primary school, raising the age at first marriage, and sensitizing the community and girls on the importance of education. Attempts to discourage female circumcision would currently be viewed as cultural imperialism, as uncircumcised girls are shunned and rarely get marriage partners.
(m) Educate the communities on the deleterious socioeconomic effects of excessive consumption of
traditional brew (e.g. health, crowding out essential expenditures, low labour inputs, etc).
CHALLENGES AND CONSTRAINTS 6.30. Some of the challenges and constraints that AAK faces include: (a) High community expectations which might lead to low participation. This is mainly attributed to
AAK’s delay in implementing visible projects during its 18 months presence in the location. (b) Misunderstanding about AAK’s mission due to the process of collecting case histories for
sponsorship funding.
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(c) Stoppage of CORPs remuneration which reduced their morale. Some discontinued their support to the programme, and are a source of strain between AAK and the community. It was premature to handover CORPs remuneration to the community before AAK had made substantial development in the area.
(d) Bomet district’s power structure became unipolar after the December 1997 general elections. (e) The area is largely a zone of the ruling party (KANU), and AAK will have to demonstrate
political neutrality. The process of empowering the poor might be interpreted as a veiled process of introducing opposition politics in the area.
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Davies, Susanna, “Plantations and the Rural Economy: Poverty, Employment and Food Security in Kenya”, IDS Bulletin, 18(2), 1987 Donovan, Michael, “Capturing the Land: Kipsigis Narratives of Progress”, Comparative Studies in Society and History, 38(4), October 1996 Evans-Pritchard, E. E., “The Political Structure of the Nandi-Speaking Peoples of Kenya”, Africa: Journal of the International African Institute, 13(3), July 1940 Fish, B.C., and G.W. Fish, The Kalenjin Heritage: Traditional, Religious and Social Practices, Africa Gospel Church (Kericho) and World Gospel Mission (Indiana), 1995 Faulkner, D.E., Notes on Animal Health and Industry for Africans, Government Printer, Nairobi (second edition), 1957 Fletcher, John Madison, “An Experimental Study of Stuttering”, The American Journal of Psychology, 25(2), April 1914 Harkness, Sara, and Charles M. Super, “The Ties That Bind: Social Networks of Men and Women in a Kipsigis Community of Kenya”, Ethos, 29(3), September 2001 Hotchkiss, W.R., Then and Now in Kenya Colony, New York, 1937 Huntingford, G.W.B., “The Nandi Pororiet”, The Journal of the Royal Anthropological Institute of Great Britain and Ireland, 65, January-June 1935 International Labour Office, Current International Recommendations on Labour Statistics, Geneva, 1988 Jaetzold, R. and H. Schmidt, Farm Management Handbook of Kenya (Volume II: Natural Conditions and Farm Management Information: Part A: West Kenya; Part B: Central Kenya; Part C: East Kenya), Ministry of Agriculture, Nairobi, Kenya, 1982 Kenya, Bomet District Development Plan, 1997-2001, Office of the Vive-President and Ministry of Planning and National Development, Government Printer, Nairobi, 1997 Kenya, Prioritized Divisional Extension Work-Plan: Bomet District, Ministry of Agriculture, Bomet, April 1997 Kenya, Central Bureau of Statistics, Kenya Population Census, 1989: Volumes I & II, Government Printer, Nairobi, 1994 Kenya, Bomet District Development Plan, 1994-96, Office of the Vive-President and Ministry of Planning and National Development, Government Printer, Nairobi, 1994 Kenya, The Districts and Provinces Act, 1992, Kenya Gazette Supplement No 53, 26 June 1992, Government Printer, Nairobi, 1992 Kenya, Central Bureau of Statistics, Economic Survey 1991 (Chapter 3: The 1989 Population Census Provisional Results), Government Printer, Nairobi, 1991 Kenya, Ministry of Agriculture, Fertilizer Use Recommendation Project: Kericho District, National Agricultural Laboratories, 1987 Kish, Leslie, Statistical Design for Research, John Wiley & Sons, Inc., New York, 1987
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Kish, Leslie, Survey Sampling, John Wiley & Sons, Inc., New York, 1965 Kratz, Corinne A., “Are the Okiek Really Masai? Or Kipsigis? Or Kikuyu?” Cahiers d’Études Africaines, 20(79), 1980 Lura, Russell, “Population Change in Kericho District, Kenya: An Example of Fertility Increase in Africa”, African Studies Review, 28(1), March 1985 Macro International Inc., Sampling Manual. DHS-III Basic Documentation No. 6, Calverton, Maryland, 1996 Marlowe, F., “Paternal investment and the human mating system”, Behavioural Processes, volume 51, 2000 Moser, C.A. and G. Kalton, Survey Methods in Social Investigation, Heinemann Educational Books, London 1979 Mukui, John T., “Kenya: Poverty Profiles, 1982-92”, Consultant Report Prepared for the World Bank and the Ministry of Planning and National Development, March 1994 Mwanzi, H.A., A History of the Kipsigis, Kenya Literature Bureau, Nairobi, 1977 Narayan, D. and D. Nyamwaya, A Participatory Poverty Assessment: Kenya, British ODA and UNICEF, June 1995 Ochieng’, W.R., An Outline History of the Rift Valley of Kenya, Kenya Literature Bureau, Nairobi, 1975 Orchardson, I.Q., The Kipsigis, East African Literature Bureau, 1961 Orchadson, I. Q., “Future development of the Kipsigis with special reference to Land tenure”, Journal of the East Africa and Uganda Natural History Society, 1935 Orchadson, I. Q., “Religious beliefs and practices of the Kipsigis”, Journal of the East Africa and Uganda Natural History Society, 1933 Orchadson, I. Q., “Notes on the marriage customs of the Kipsigis”, Journal of the East Africa and Uganda Natural History Society, 1931 Platt, B.S., Tables of Representative Values of Foods Commonly Used in Tropical Countries, London School of Hygiene and Tropical Medicine, London, 1962 Ridley, Matt, The Red Queen: Sex and the Evolution of Human Nature, Penguin Books Ltd, 1993 Sehmi, J.K., National Food Composition Tables and the Planning of Satisfactory Diets in Kenya, Government Printer, Nairobi, 1993 Sørensen, Anne, “Women's Organisations among the Kipsigis: Change, Variety and Different Participation”, Africa: Journal of the International African Institute, 62(4), 1992 Subramanian, Shankar, and Angus Deaton, “The Demand for Food and Calories”, Journal of Political Economy, 104(1), February 1996 Suchman, Edward A., “Social Patterns of Illness and Medical Care”, Journal of Health and Social Behavior, 6(1), 1965
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Suchman, Edward A., “Stages of Illness and Medical Care “, Journal of Health and Social Behavior, 6(3), 1965 Suchman, E.A., Sociology and the Field of Public Health, Russell Sage Foundation, New York, 1963 Suda, Collette A., “Fertility and the Status of Women in Kericho District: Reflections on Some Key Reproductive Issues”, Kenya Journal of Sciences: Humanities and Social Sciences, 4(1), 1997 Toweett, Taaitta, Oral Traditional History of the Kipsigis, Kenya Literature Bureau, Nairobi, 1979 United Nations, National Household Survey Capability Programme, Household Income and Expenditure Surveys: a technical study, New York, 1989 United Nations, Studies in Methods: Handbook of Household Surveys, New York, 1984 von Bülow, Dorthe, and Anne Sørensen, “Gender and Contract Farming: Tea Outgrower Schemes in Kenya”, Review of African Political Economy, No. 56, March 1993 von Bülow, Dorthe, “Bigger than Men? Gender Relations and their Changing Meaning in Kipsigis Society, Kenya”, Africa: Journal of the International African Institute, 62(4), 1992 Ward, C.E., “Sun-worship amongst the Kipsigis or Lumbwa Tribe”, Journal of the East Africa and Uganda Natural History Society, 1926 Weisner, Thomas S., “One Family, Two Households: Rural-Urban Kin Networks in Nairobi”, University of Nairobi, 1970 White, Douglas R., “Questioning the Correlational Evidence for Kipsigis Wealth as a Cause of Reproductive Success Rather than Polygyny as a Cause of Both Extra Children and Extra Wealth”, American Anthropologist, New Series, 91(1), March 1989 White, Douglas R., “Rethinking Polygyny: Co-Wives, Codes, and Cultural Systems”, Current Anthropology, 29(4), 1988
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LIST OF ENUMERATORS Isaac Lang’at Community Resource Person/AAK, Farmer Leah Mitei Community Resource Person/AAK, FarmerNancy Cheborgei Community Resource Person/AAK, FarmerRachel Kilel Primary School Teacher Richard Kimeto Community Resource Person/AAK, Farmer David Lang’at PTA Teacher Joel Ruto Community Resource Person/AAK, Small-scale trader Cecilia C. Kasembe Nursery School TeacherZipporah Chepkoech Primary School Teacher Julius Tonui Primary School Teacher Joseah Kenduiwa Assistant Primary School Inspector (APSI) John Ruto Location Agricultural Extension Officer
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PEOPLE CONTACTED Mercy Karanja Project Coordinator/AAK-BometSolomon Kipkurui Assistant Project Coordinator/AAK-BometRichard Kimeto CRP-AAKKibiti Rintari District Commissioner, BometFrancis Nyagambi District Development Officer, BometAugustine Kenduiwo District Crops Officer, BometJ.M. Wachira District Marketing Officer, BometDavid K. Tonui District Livestock Production Officer, BometR.I.M. Chanzu District Education Officer, BometKipchumba Komen Divisional Agricultural Extension Officer, SigorJoshua K. Rono Area Education Officer, SigorJackson M. Okonji Divisional Veterinary Officer, SigorRobinson K. Rotich Chief, Lelaitich locationElijah Mutai Assistant Chief, Lelaitich sub-locationJoseah Kenduiwa Assistant Primary School Inspector (APSI), Lelaitich location John K. Ruto Location Agricultural Extension Officer, Lelaitich location John K. Rotich Location Forest Extension OfficerCharles K. Bor Junior Livestock Health Officer, LelaitichJ.C. Tuimising Businessman, Kinyang’a MarketJoseph Koech District Agricultural Officer, Bomet
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STATISTICAL APPENDIX Table 1: Number of Households by Village in Lelaitich Location Table 2: Bomet District: Agricultural Potential Table 3: Annual per Capita Income in Bomet District (Shs) Table 4: Crop Production in Bomet District (tons) Table 5: Livestock Population in Bomet District: 1996 Table 6: Pre School Enrolment in Bomet District Table 7A: Primary School Enrolment in Bomet District Table 7B: Primary School Enrolment in Bomet district: Progression Rates Based on Cross-section Data Table 8: Enrolment in Adult Education in Bomet District Table 9: Distribution of Households by Interview Status Table 10: Distribution of Responding Population by Age Group and Sex Table 11: Estimates of Total Population Using Weighted Data Table 12: Distribution of the Responding Population by Sex and Relation to Head Table 13: Distribution of the Responding Population by Sex and Marital Status Table 14: Distribution of the Responding Population by Marital Status, Age Group and Sex Table 15: Distribution of the Population Attending School Table 16: Distribution of the Population Not At School, > 6 Years Table 17: Education Profile of the Population, > 6 Years Table 18: Age-Grade Mismatch in the Education Cycle: Lelaitich Location Table 19: Primary School Enrolment Table 20: Literacy Status of the Non-school Population, > 8 Years Table 21: Reasons for Dropping Out of Primary School for Period 1993 1996 Table 22: Distribution of the Population by Place of Birth Table 23: Distribution of Group Membership by Type of Self-Help Group (15+ years) Table 24: Types of Sickness in the Preceding Two Weeks by Age Table 25: Number of Disabilities in the Responding Population Table 26: Distribution of Under-Fives by Place of Delivery Table 27: Distribution of Under-Fives by Delivering Personnel Table 28: Immunization Status by Sex, 11 59 Months Table 29: Distribution of Under-Fives by Months Breastfed Table 30: Distribution of Under-Fives by Type of First Supplement Table 31: Construction Materials of the Main Residential Structure Table 32: Combination of Construction Materials of the Main Residential Structure Table 33: Distribution of Households by Ventilation and Human-Animal Interaction Table 34: Distribution of Households by Source of Water and Mean Distance to Source Table 35: Distribution of Households by Distance to Water Sources Table 36: Distribution of Households by Household Members Mainly Responsible for Collecting Water Table 37: Distribution of Households by Disposal of Rubbish and Human Excreta Table 38: Distribution of Households by Sources of Cooking and Lighting Fuels Table 39: Distribution of Households by Whether Own Selected Assets Table 40: Distribution of Households by Mean Distance to Selected Amenities (km) Table 41A: Crop Production Costs per Household: Lelaitich Sub location (Shs) Table 41B: Crop Production Costs per Household: Kapsabul Sub location (Shs) Table 41C: Crop Production Costs per Household: Lugumek Sub location (Shs) Table 41D: Crop Production Costs per Household: Lelaitich Location (Shs) Table 42A: Crop Production per Household: Lelaitich Sub location
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Table 42B: Crop Production per Household: Kapsabul Sub location Table 42C: Crop Production per Household: Lugumek Sub location Table 42D: Crop Production per Household: Lelaitich Location Table 43: Distribution of Households by Farm Management Practices Table 44A: Livestock Production and Disposal per Household: Lelaitich Sub location Table 44B: Livestock Production and Disposal per Household: Kapsabul Sub location Table 44C: Livestock Production and Disposal per Household: Lugumek Sub location Table 44D: Livestock Production and Disposal per Household: Lelaitich Location Table 45A: Livestock Production Costs per Household: Lelaitich Sub location (Shs) Table 45B: Livestock Production Costs per Household: Kapsabul Sub location (Shs) Table 45C: Livestock Production Costs per Household: Lugumek Sub location (Shs) Table 45D: Livestock Production Costs per Household: Lelaitich Location (Shs) Table 46: Household Income by Sub location (Shs) Table 47: Income per Capita by Sub location (Shs) Table 48: Household Income by Sub location and Sex of Household Head (Shs) Table 49: Household Income by Sub location and Education of Household Head (Shs) Table 50: Household Income by Sub location and Age of Household Head (Shs) Table 51: Income per Capita by Sub location and Sex of Household Head (Shs) Table 52: Income per Capita by Sub location and Education of Household Head (Shs) Table 53: Income per Capita by Sub location and Age of Household Head (Shs) Table 54: Households by Land Owned and Accessed (acres) Table 55: Households by Land Owned and Accessed by Sex of Household Head (acres) Table 56: Household by Land Owned and Accessed by Education of Household Head (acres) Table 57: Households by Land Owned and Accessed by Age of Household Head (acres) Table 58: Household Consumption per Month (Shs) Table 59: Household Consumption Patterns (%) Table 60: Household Consumption per Capita (Shs) Table 61: Household Consumption per Capita (%) Table 62: Estimated Calorie and Protein Availability per Adult Equivalent
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Table 1: Number of Households by Village in Lelaitich Location LELAITICH KAPSABUL LUGUMEK Village Households Village Households Village HouseholdsLelaitich 42 Simotwet 52 Lugumek Central 38Cheptare 57 Cheboiwo 29 Chebitoik 49Mabutek 57 Kapinderem 39 Kosia South 57Terta 30 Chepkirabach 33 Kosia North 55Chepkebit 36 Cheptebes 40 Chebunge 48Kapsasian South 21 Chemengwa 33 Lugumek North 38Kapsasian North 29 Cheronye 33 Koita 35Kapkwen (Nyak) 20 Boreiwek 37 Lugumek West 38Nyakichiwa 26 Chematich 42 Kapchemoino 32Sumelei 36 Uswet 37 Chepkoin 61Koita 21 Kaptororgo 33 Kipsirichet 31Kapkwen-Lelaitich 51 Kapkoros 41Kipsirat 49 Kapsabul 43 Simotwet 33 Kiptenden 36Total 508 528 482Source: ACTIONAID-Kenya Table 2: Bomet District: Agricultural Potential DIVISION Area (sq
km) Population AEZ/Area (sq km) Holdings Agricultural land
LH1 LH2 LH3 UM3 UM4 UM5 Area (sq km)
%
Longisa 262 72,710 110 93 59 11,285 235 89.7Sigor 214 53,165 75 118 21 6,976 193 90.2Siongiroi 279 42,607 186 93 5,590 224 80.3Ndanai 161 69,629 59 102 9,135 153 95.0Sotik 421 94,015 84 140 197 12,335 379 90.0Bomet Central
365 95,845 243 122 12,576 336 92.1
Konoin 493 71,071 493 9,325 468 94.9Kimulot 416 57,118 416 7,495 395 95.0Total 2,611 556,160 1,236 431 0 653 270 21 74,717 2,383 91.3Sigor Division
Kaboson 56.5 Lelaitich 39.2 Sigor 53.7 Sigor North 64.6 Lelaitich Location
Lugumek 14.8 Kapsabul 14.4 Lelaitich 10.0 Legends: LH1: Tea/ dairy zone LH2: Wheat/ maize/ pyrethrum zone LH3: Wheat/ maize/ barley zone UM1: Coffee/ tea zone UM2: Coffee zone UM3: Marginal coffee zone UM4: Sunflower/ maize zone UM5: Livestock/ sorghum zone Source: Ministries of Land and Agriculture, Bomet district; Bomet District Development Plan 1997-2001
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Table 3: Annual per Capita Income in Bomet District (Shs) DIVISION 1992 1993 1994 1995 1996Longisa 3,970 4,734 5,302 4,418 3,096Sigor 4,447 5,333 6,352 5,012 3,495Siongiroi 4,805 5,922 7,041 5,720 3,889Ndanai 3,540 4,013 4,894 3,865 2,836Sotik 7,702 7,915 8,169 8,210 6,251Bomet Central 17,861 16,144 16,262 17,778 14,945Konoin 16,740 14,432 14,332 16,429 13,269Kimulot 21,827 19,112 18,723 21,315 16,874Total 10,516 10,012 10,391 10,719 8,453 Note: 1992 figures do not include income from businesses, while 1996 figures do not include income from both businesses and the values of marketed livestock products. Source: Bomet District Development Plan 1997-2001
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Table 4: Crop Production in Bomet district (tons) DIVISION Maize Beans Finger millet
1,994 1,995 1,994 1,995 1,994 1,995 Ha Prod. Yield Ha Prod. Yield Ha Prod. Yield Ha Prod. Yield Ha Prod. Yield Ha Prod. Yield
Longisa 5,974 19,117 3.2 5,350 16,050 3.0 1,458 729 0.5 1,654 827 0.5 257 129 0.5 235 94 0.4Sigor 5,777 17,331 3.0 5,500 15,400 2.8 1,970 985 0.5 2,500 1,200 0.5 115 58 0.5 58 23 0.4Siongiroi 4,807 16,344 3.4 4,038 11,306 2.8 966 483 0.5 800 320 0.4 72 22 0.3 60 18 0.3Ndanai 6,500 20,800 3.2 6,400 17,920 2.8 1,200 540 0.5 420 168 0.4 200 80 0.4 205 82 0.4Sotik 5,569 18,934 3.4 4,291 12,872 3.0 905 407 0.5 500 250 0.5 67 30 0.4 55 28 0.5Bomet Central 6,293 18,879 3.0 5,331 15,992 3.0 922 461 0.5 990 495 0.5 70 28 0.4 173 69 0.4Konoin 3,241 9,723 3.0 2,201 6,382 2.9 420 189 0.5 524 236 0.5 100 70 0.7 48 19 0.4Kimulot 2,057 6,171 3.0 1,780 5,162 2.9 425 191 0.5 281 126 0.5 51 21 0.4 16 5 0.3Total 40,218 127,299 3.2 34,890 101,083 2.9 8,266 3,985 0.5 7,669 3,622 0.5 933 437 0.5 850 338 0.4 Source: Ministry of Agriculture, Bomet Table 5: Livestock Population in Bomet District: 1996 DIVISION Dairy/ high
grade Zebu Total Wool
sheep Hair sheep
Meat goats
Dairy goats
Local birds
Exotic Total Rabbits KTBH Traditional log hives
Honey (kgs)
Longisa 0 0 0 1,500 12,000 10,000 0 42,000 7,000 49,000 105 189 438 7,500Sigor 1,500 40,000 41,500 1,000 12,000 15,000 0 15,000 500 15,500 300 120 1,400 13,000Siongiroi 28,146 27,000 55,146 1,500 15,000 10,000 600 65,000 4,000 69,000 200 292 2,000 11,000Ndanai 26,730 7,430 34,160 1,000 9,450 15,000 100 65,000 2,000 67,000 100 150 400 8,000Sotik 38,000 18,500 56,500 0 16,500 10,000 0 70,000 10,000 80,000 80 89 200 3,000Bomet Central
25,000 40,000 65,000 5,360 10,000 10,000 80 45,000 2,180 47,180 100 144 2,500 22,000
Konoin 35,000 32,300 67,300 2,000 10,000 1,900 100 32,000 1,000 33,000 630 89 420 6,500Kimulot 19,900 2,080 21,980 0 10,000 3,100 0 8,800 1,100 9,900 100 80 100 2,500Total 174,276 167,310 341,586 12,360 94,950 75,000 880 342,800 27,780 370,580 1,615 1,153 7,458 73,500 Source: Ministry of Agriculture, Bomet
53
Table 6: Pre-School Enrolment in Bomet district DIVISION 1995 1996
Female Male Total Female Male Total Longisa 1,984 1,977 3,961 2,234 2,277 4,511Sigor 1,451 752 2,203 1,650 812 2,462Siongiroi 1,070 1,101 2,171 1,100 1,172 2,272Ndanai 788 871 1,659 908 1,020 1,928Sotik 2,136 2,035 4,171 2,321 2,112 4,433Bomet Central 2,269 2,328 4,597 2,769 2,828 5,597Konoin 894 866 1,760 1,074 1,060 2,134Kimulot 1,380 1,338 2,718 1,535 1,640 3,175Total 11,972 11,268 23,240 13,591 12,921 26,512 Source: District Education Officer, Bomet
54
Table 7A: Primary School Enrolment in Bomet district DIVISION Std 1 Std 2 Std 3 Std 4 Std 5 Std 6 Std 7 Std 8 Total
F M F M F M F M F M F M F M F M F M Total Longisa 1,737 1,754 1,608 1,562 1,433 1,395 1,237 1,229 1,109 1,084 1,205 1,109 1,343 1,258 480 917 10,152 10,308 20,460Sigor 1,027 1,074 809 847 782 782 774 714 685 689 691 613 695 686 433 643 5,896 6,048 11,944Siongiroi 1,376 1,515 1,285 1,266 1,083 1,058 1,130 1,067 966 931 921 868 926 1,015 558 683 8,245 8,403 16,648Ndanai 762 801 761 763 715 723 653 613 613 470 592 504 662 630 291 439 5,049 4,943 9,992Sotik 2,168 2,191 1,891 1,902 1,702 1,723 1,791 1,735 1,548 1,590 1,603 1,433 1,824 1,564 1,030 1,244 13,557 13,382 26,939Bomet Central 2,409 2,575 2,117 2,216 2,102 2,096 1,907 1,944 1,681 1,746 1,706 1,596 2,020 1,869 1,071 1,187 15,013 15,229 30,242Konoin 1,403 1,489 1,184 1,225 1,098 1,096 1,049 1,034 947 850 969 817 936 948 567 732 8,153 8,191 16,344Kimulot 1,442 1,562 1,095 1,196 938 1,035 838 927 668 716 584 665 603 726 342 489 6,510 7,316 13,826Total 12,324 12,961 10,750 10,977 9,853 9,908 9,379 9,263 8,217 8,076 8,271 7,605 9,009 8,696 4,772 6,334 72,575 73,820 146,395Memorandum item: Lelaitich
194 187 119 161 139 151 119 110 121 114 101 87 84 113 35 91 912 1,014 1,926
Table 7B: Primary School Enrolment in Bomet district: Progression Rates Based on Cross-section Data DIVISION Std 1 Std 2 Std 3 Std 4 Std 5 Std 6 Std 7 Std 8
F M F M F M F M F M F M F M F M TotalLongisa 100.00 100.00 92.57 89.05 82.50 79.53 71.21 70.07 63.85 61.80 69.37 63.23 77.32 71.72 27.63 52.28 40.02Sigor 100.00 100.00 78.77 78.86 76.14 72.81 75.37 66.48 66.70 64.15 67.28 57.08 67.67 63.87 42.16 59.87 51.21Siongiroi 100.00 100.00 93.39 83.56 78.71 69.83 82.12 70.43 70.20 61.45 66.93 57.29 67.30 67.00 40.55 45.08 42.93Ndanai 100.00 100.00 99.87 95.26 93.83 90.26 85.70 76.53 80.45 58.68 77.69 62.92 86.88 78.65 38.19 54.81 46.71Sotik 100.00 100.00 87.22 86.81 78.51 78.64 82.61 79.19 71.40 72.57 73.94 65.40 84.13 71.38 47.51 56.78 52.17Bomet Central 100.00 100.00 87.88 86.06 87.26 81.40 79.16 75.50 69.78 67.81 70.82 61.98 83.85 72.58 44.46 46.10 45.30Konoin 100.00 100.00 84.39 82.27 78.26 73.61 74.77 69.44 67.50 57.09 69.07 54.87 66.71 63.67 40.41 49.16 44.92Kimulot 100.00 100.00 75.94 76.57 65.05 66.26 58.11 59.35 46.32 45.84 40.50 42.57 41.82 46.48 23.72 31.31 27.66Total 100.00 100.00 87.23 84.69 79.95 76.44 76.10 71.47 66.67 62.31 67.11 58.68 73.10 67.09 38.72 48.87 43.92Memorandum item: Lelaitich 100.00 100.00 61.34 86.10 71.65 80.75 61.34 58.82 62.37 60.96 52.06 46.52 43.30 60.43 18.04 48.66 33.07 Source: District Education Officer, Bomet
55
Table 8: Enrolment in Adult Education in Bomet district DIVISION 1993 1994 1995 1996
Female Male Total Female Male Total Female Male Total Female Male Total Longisa 138 10 148Sigor 163 9 172 112 10 122 149 8 157 100 10 110Siongiroi 102 7 109 70 19 89 98 28 126 89 25 114Ndanai 96 21 117 94 17 111 93 11 104 115 22 137Sotik 462 85 547 429 110 539 416 91 507 467 93 560Bomet Central 120 17 137 181 27 208 130 31 161 108 15 123Konoin 163 26 189 161 30 191 241 43 284 192 20 212Kimulot 195 20 215 150 20 170 192 20 212 162 20 182Total 1,439 195 1,634 1,197 233 1,430 1,319 232 1,551 1,233 205 1,438 Source: District Education Officer, Bomet
56
Table 9: Distribution of Households by Interview Status
Completed Partial Vacant Away Refusal Impaired Total % CompletedLELAITICH 63 1 6 1 3 1 75 84.0Lelaitich 5 1 0 0 0 0 6 83.3Cheptare 8 0 1 0 0 0 9 88.9Mabutek 5 0 0 1 0 1 7 71.4Terta 4 0 1 0 0 0 5 80.0Chepkebit 5 0 0 0 0 0 5 100.0Kapsasian South 3 0 0 0 0 0 3 100.0Kapsasian North 4 0 1 0 0 0 5 80.0Kapkwen Nyak 3 0 0 0 0 0 3 100.0Nyakichiwa 4 0 0 0 0 0 4 100.0Sumelei 2 0 1 0 2 0 5 40.0Koita 1 0 1 0 1 0 3 33.3Kapkwen Lelaitich 8 0 0 0 0 0 8 100.0Kipsirat 7 0 0 0 0 0 7 100.0Simotwet 4 0 1 0 0 0 5 80.0KAPSABUL 68 0 4 0 5 1 78 87.2Simotwet 4 0 1 0 3 0 8 50.0Cheboiwo 4 0 0 0 0 0 4 100.0Kapinderem 4 0 1 0 1 0 6 66.7Chepkirabach 5 0 0 0 0 0 5 100.0Cheptebes 6 0 0 0 0 0 6 100.0Chemengwa 5 0 0 0 0 0 5 100.0Cheronye 3 0 0 0 1 0 4 75.0Boreiwek 5 0 1 0 0 0 6 83.3Chematich 5 0 0 0 0 1 6 83.3Uswet 5 0 0 0 0 0 5 100.0Kaptororgo 5 0 0 0 0 0 5 100.0Kapkoros 6 0 1 0 0 0 7 85.7Kapsabul 6 0 0 0 0 0 6 100.0Kiptenden 5 0 0 0 0 0 5 100.0LUGUMEK 66 0 3 0 3 0 72 91.7Lugumek Central 6 0 0 0 0 0 6 100.0Chebitoik 6 0 1 0 0 0 7 85.7Kosia South 8 0 0 0 1 0 9 88.9Kosia North 7 0 1 0 0 0 8 87.5Chebunge 6 0 0 0 1 0 7 85.7Lugumek North 5 0 1 0 0 0 6 83.3Koita 5 0 0 0 0 0 5 100.0Lugumek West 6 0 0 0 0 0 6 100.0Kapchemoino 4 0 0 0 0 0 4 100.0Chepkoin 10 0 0 0 0 0 10 100.0Kipsirichet 3 0 0 0 1 0 4 75.0TOTAL 197 1 13 1 11 2 225 87.6TOTAL (%) 87.6 0.4 5.8 0.4 4.9 0.9 100.0
57
Table 10: Distribution of Responding Population by Age Group and Sex 0-4 5-9 10-14 15-24 25-39 40-59 60+ Total
LELAITICH Male 25 34 32 43 30 14 9 187 Female 27 36 30 31 33 15 13 185 Total 52 70 62 74 63 29 22 372
Lelaitich Male 2 7 3 4 3 1 0 20 Female 2 1 2 4 3 2 0 14
Cheptare Male 2 3 6 6 5 1 1 24 Female 3 4 5 5 3 3 2 25
Mabutek Male 3 1 2 2 2 1 1 12 Female 1 5 2 2 1 1 1 13
Terta Male 1 2 2 4 1 2 0 12 Female 0 3 5 3 2 1 1 15
Chepkebit Male 2 5 3 5 2 3 0 20 Female 3 3 3 2 1 2 0 14
Kapsasian South Male 2 3 3 3 1 2 0 14 Female 2 2 2 0 2 1 0 9
Kapsasian North Male 3 2 1 0 2 1 0 9 Female 3 3 1 0 4 0 1 12
Kapkwen Nyak Male 2 1 0 1 2 0 0 6 Female 2 0 0 1 1 0 1 5
Nyakichiwa Male 1 2 2 4 2 0 2 13 Female 2 4 2 3 3 1 2 17
Sumelei Male 0 0 0 1 0 0 1 2 Female 0 1 1 0 2 0 1 5
Koita Male 0 0 1 1 2 0 1 5 Female 0 0 0 0 0 1 0 1
Kapkwen Lelaitich Male 2 3 3 8 3 3 1 23 Female 3 3 4 2 5 1 1 19
Kipsirat Male 3 3 6 3 3 0 1 19 Female 3 6 3 4 4 2 1 23
Simotwet Male 2 2 0 1 2 0 1 8 Female 3 1 0 5 2 0 2 13
KAPSABUL Male 31 41 26 52 25 22 11 208 Female 30 30 33 45 29 19 6 192 Total 61 71 59 97 54 41 17 400
Simotwet Male 2 4 2 1 1 1 0 11 Female 2 0 3 1 3 0 0 9
Cheboiwo Male 2 3 2 3 2 1 1 14 Female 4 3 3 4 2 1 0 17
Kapinderem Male 4 2 2 0 2 0 0 10 Female 0 2 1 0 3 0 1 7
Chepkirabach Male 0 1 1 5 0 4 1 12 Female 1 2 4 0 3 1 0 11
Cheptebes Male 3 6 1 5 4 2 1 22 Female 0 3 3 6 1 2 1 16
Chemengwa Male 7 5 4 3 3 2 0 24 Female 3 3 2 4 4 1 0 17
Cheronye Male 1 2 0 5 0 3 0 11 Female 2 2 4 2 1 2 0 13
Boreiwek Male 1 1 0 5 1 1 2 11 Female 1 2 1 6 0 2 1 13
Chematich Male 1 3 4 3 2 3 0 16 Female 3 4 2 3 1 1 0 14
Uswet Male 3 4 2 5 3 3 0 20 Female 3 4 6 5 3 3 0 24
Kaptororgo Male 1 0 1 6 1 0 3 12 Female 1 1 0 3 1 2 1 9
Kapkoros Male 2 2 3 4 2 0 1 14
58
0-4 5-9 10-14 15-24 25-39 40-59 60+ Total Female 3 3 0 1 2 2 2 13
Kapsabul Male 2 5 1 4 2 2 0 16 Female 4 1 3 6 2 1 0 17
Kiptenden Male 2 3 3 3 2 0 2 15 Female 3 0 1 4 3 1 0 12
LUGUMEK Male 33 42 38 54 23 17 7 214 Female 29 20 30 30 27 16 15 167 Total 62 62 68 84 50 33 22 381
Lugumek Central Male 6 7 7 4 2 2 0 28 Female 4 3 2 5 5 2 1 22
Chebitoik Male 2 2 6 4 2 2 0 18 Female 2 2 1 1 2 2 0 10
Kosia South Male 5 9 4 4 4 1 1 28 Female 3 3 2 3 4 1 2 18
Kosia North Male 5 3 5 6 2 3 0 24 Female 1 3 4 5 3 1 1 18
Chebunge Male 1 1 0 2 1 1 2 8 Female 2 2 2 3 2 0 3 14
Lugumek North Male 2 0 1 4 2 1 1 11 Female 2 0 4 2 0 1 2 11
Koita Male 4 5 4 6 2 1 1 23 Female 1 1 2 1 2 1 2 10
Lugumek West Male 2 5 2 9 2 2 1 23 Female 4 0 4 5 2 3 0 18
Kapchemoino Male 1 3 1 5 1 2 0 13 Female 2 2 3 1 0 3 0 11
Chepkoin Male 4 6 4 6 4 1 1 26 Female 7 1 6 3 6 1 4 28
Kipsirichet Male 1 1 4 4 1 1 0 12 Female 1 3 0 1 1 1 0 7
TOTAL Male 89 117 96 149 78 53 27 609 Female 86 86 93 106 89 50 34 544 Total 175 203 189 255 167 103 61 1,153
PERCENT Lelaitich Male 13.37 18.18 17.11 22.99 16.04 7.49 4.81 100.00
Female 14.59 19.46 16.22 16.76 17.84 8.11 7.03 100.00 Total 13.98 18.82 16.67 19.89 16.94 7.80 5.91 100.00
Kapsabul Male 14.90 19.71 12.50 25.00 12.02 10.58 5.29 100.00 Female 15.63 15.63 17.19 23.44 15.10 9.90 3.13 100.00 Total 15.25 17.75 14.75 24.25 13.50 10.25 4.25 100.00
Lugumek Male 15.42 19.63 17.76 25.23 10.75 7.94 3.27 100.00 Female 17.37 11.98 17.96 17.96 16.17 9.58 8.98 100.00 Total 16.27 16.27 17.85 22.05 13.12 8.66 5.77 100.00
TOTAL (%) Male 14.61 19.21 15.76 24.47 12.81 8.70 4.43 100.00 Female 15.81 15.81 17.10 19.49 16.36 9.19 6.25 100.00 Total 15.18 17.61 16.39 22.12 14.48 8.93 5.29 100.00
SEX RATIO (%) Lelaitich 92.6 94.4 106.7 138.7 90.9 93.3 69.2 101.1 Kapsabul 103.3 136.7 78.8 115.6 86.2 115.8 183.3 108.3 Lugumek 113.8 210.0 126.7 180.0 85.2 106.3 46.7 128.1 Total 103.5 136.0 103.2 140.6 87.6 106.0 79.4 111.9
59
Table 11: Estimates of Total Population using Weighted Data Male Female Total
Lelaitich 1,482 1,449 2,931Kapsabul 1,609 1,491 3,099Lugumek 1,553 1,201 2,755Total 4,644 4,141 8,785 Table 12: Distribution of the Responding Population by Sex and Relation to Head
Head male
Head female
Spouse Son Daughter Other relative
Non-relative
Total Male-headed (%)
LELAITICH 45 18 48 133 111 17 0 372 71.4Lelaitich 3 2 3 17 9 0 0 34 60.0Cheptare 4 4 4 19 14 4 0 49 50.0Mabutek 4 1 4 8 8 0 0 25 80.0Terta 2 2 2 8 11 2 0 27 50.0Chepkebit 5 0 5 14 8 2 0 34 100.0Kapsasian South
3 0 3 11 6 0 0 23 100.0
Kapsasian North
3 1 4 6 7 0 0 21 75.0
Kapkwen Nyak 2 1 2 4 2 0 0 11 66.7Nyakichiwa 3 1 4 10 12 0 0 30 75.0Sumelei 1 1 1 1 3 0 0 7 50.0Koita 1 0 1 4 0 0 0 6 100.0Kapkwen Lelaitich
7 1 8 14 10 2 0 42 87.5
Kipsirat 4 3 4 13 13 5 0 42 57.1Simotwet 3 1 3 4 8 2 0 21 75.0KAPSABUL 59 9 57 143 119 12 1 400 86.8Simotwet 3 1 3 8 5 0 0 20 75.0Cheboiwo 4 0 4 10 13 0 0 31 100.0Kapinderem 2 2 2 8 3 0 0 17 50.0Chepkirabach 4 1 4 7 7 0 0 23 80.0Cheptebes 6 0 5 15 8 4 0 38 100.0Chemengwa 5 0 5 16 9 5 1 41 100.0Cheronye 3 0 3 8 10 0 0 24 100.0Boreiwek 4 1 4 6 6 3 0 24 80.0Chematich 5 0 3 11 11 0 0 30 100.0Uswet 4 1 5 16 18 0 0 44 80.0Kaptororgo 5 0 5 7 4 0 0 21 100.0Kapkoros 3 3 3 11 7 0 0 27 50.0Kapsabul 6 0 6 10 11 0 0 33 100.0Kiptenden 5 0 5 10 7 0 0 27 100.0LUGUMEK 51 15 54 155 88 18 0 381 77.3Lugumek Central
5 1 8 23 12 1 0 50 83.3
Chebitoik 4 2 3 14 5 0 0 28 66.7Kosia South 6 2 6 22 10 0 0 46 75.0Kosia North 6 1 6 18 11 0 0 42 85.7Chebunge 5 1 5 3 6 2 0 22 83.3Lugumek North 4 1 4 5 4 4 0 22 80.0Koita 4 1 4 17 4 3 0 33 80.0Lugumek West 4 2 4 19 12 0 0 41 66.7Kapchemoino 3 1 3 10 7 0 0 24 75.0Chepkoin 7 3 8 15 13 8 0 54 70.0Kipsirichet 3 0 3 9 4 0 0 19 100.0TOTAL 155 42 159 431 318 47 1 1,153 78.7TOTAL (%) 13.4 3.6 13.8 37.4 27.6 4.1 0.1 100.0
60
Table 13: Distribution of the Responding Population by Sex and Marital Status
Never Married Monogamous Polygamous Unmarried Total LELAITICH Male 142 35 10 0 187
Female 118 36 12 19 185Lelaitich Male 17 2 1 0 20
Female 8 2 1 3 14Cheptare Male 20 3 1 0 24
Female 17 3 1 4 25Mabutek Male 8 3 1 0 12
Female 8 3 1 1 13Terta Male 10 1 1 0 12
Female 11 2 1 1 15Chepkebit Male 15 4 1 0 20
Female 9 4 1 0 14Kapsasian South Male 11 3 0 0 14
Female 6 3 0 0 9Kapsasian North Male 6 2 1 0 9
Female 7 2 2 1 12Kapkwen Nyak Male 4 2 0 0 6
Female 2 2 0 1 5Nyakichiwa Male 10 3 0 0 13
Female 12 3 0 2 17Sumelei Male 1 0 1 0 2
Female 3 0 1 1 5Koita Male 4 0 1 0 5
Female 0 0 1 0 1Kapkwen Lelaitich Male 16 6 1 0 23
Female 10 6 2 1 19Kipsirat Male 15 3 1 0 19
Female 16 3 1 3 23Simotwet Male 5 3 0 0 8
Female 9 3 0 1 13KAPSABUL Male 144 49 12 3 208
Female 123 48 13 8 192Simotwet Male 8 3 0 0 11
Female 5 3 0 1 9Cheboiwo Male 10 3 1 0 14
Female 13 3 1 0 17Kapinderem Male 8 2 0 0 10
Female 3 2 0 2 7Chepkirabach Male 7 3 2 0 12
Female 8 1 2 0 11Cheptebes Male 14 7 0 1 22
Female 9 7 0 0 16Chemengwa Male 19 5 0 0 24
Female 12 5 0 0 17Cheronye Male 8 2 1 0 11
Female 10 2 1 0 13Boreiwek Male 5 4 2 0 11
Female 7 4 1 1 13Chematich Male 11 3 0 2 16
Female 11 3 0 0 14Uswet Male 16 3 1 0 20
Female 18 3 2 1 24Kaptororgo Male 7 2 3 0 12 Female 3 2 3 1 9Kapkoros Male 11 2 1 0 14
Female 7 3 2 1 13
61
Never Married Monogamous Polygamous Unmarried TotalKapsabul Male 10 6 0 0 16
Female 11 6 0 0 17Kiptenden Male 10 4 1 0 15
Female 6 4 1 1 12LUGUMEK Male 162 42 9 1 214
Female 97 40 15 15 167Lugumek Central Male 23 4 1 0 28
Female 13 4 5 0 22Chebitoik Male 14 3 0 1 18
Female 5 3 0 2 10Kosia South Male 22 5 1 0 28
Female 10 5 1 2 18Kosia North Male 18 6 0 0 24
Female 11 6 0 1 18Chebunge Male 3 5 0 0 8
Female 7 5 0 2 14Lugumek North Male 6 4 1 0 11
Female 7 2 1 1 11Koita Male 19 2 2 0 23
Female 5 2 2 1 10Lugumek West Male 19 2 2 0 23
Female 12 2 2 2 18Kapchemoino Male 10 3 0 0 13
Female 7 3 0 1 11Chepkoin Male 19 6 1 0 26
Female 16 6 3 3 28Kipsirichet Male 9 2 1 0 12
Female 4 2 1 0 7TOTAL Male 448 126 31 4 609
Female 338 124 40 42 544 Total 786 250 71 46 1,153
TOTAL (%) Male 73.56 20.69 5.09 0.66 100.00 Female 62.13 22.79 7.35 7.72 100.00 Total 68.17 21.68 6.16 3.99 100.00
62
Table 14: Distribution of the Responding Population by Marital Status, Age Group and Sex Never Married Monogamous Polygamous Unmarried Total
Lelaitich Male 0-4 25 0 0 0 25 5-9 34 0 0 0 34 10-14 32 0 0 0 32 15-24 42 1 0 0 43 25- 39 9 20 1 0 30 40-59 0 9 5 0 14 60+ 0 5 4 0 9 Female 0-4 27 0 0 0 27 5-9 36 0 0 0 36 10-14 30 0 0 0 30 15-24 22 7 2 0 31 25-39 3 20 4 6 33 40-59 0 6 3 6 15 60+ 0 3 3 7 13
Kapsabul Male 0-4 31 0 0 0 31 5-9 41 0 0 0 41 10-14 26 0 0 0 26 15-24 44 8 0 0 52 25-39 2 22 0 1 25 40 -59 0 17 3 2 22 60+ 0 2 9 0 11 Female 0-4 30 0 0 0 30 5-9 30 0 0 0 30 10-14 33 0 0 0 33 15-24 29 14 0 2 45 25-39 1 23 3 2 29 40-59 0 10 7 2 19 60+ 0 1 3 2 6
Lugumek Male 0-4 33 0 0 0 33 5-9 42 0 0 0 42 10-14 38 0 0 0 38 15-24 45 9 0 0 54 25-39 4 19 0 0 23 40-59 0 11 5 1 17 60+ 0 3 4 0 7 Female 0-4 29 0 0 0 29 5-9 20 0 0 0 20 10-14 30 0 0 0 30 15-24 16 13 1 0 30 25-39 2 18 3 4 27 40-59 0 6 7 3 16 60+ 0 3 4 8 15
TOTAL Male 0-4 89 0 0 0 89 5-9 117 0 0 0 117 10-14 96 0 0 0 96
63
Never Married Monogamous Polygamous Unmarried Total 15-24 131 18 0 0 149 25-39 15 61 1 1 78 40-59 0 37 13 3 53 60+ 0 10 17 0 27 Female 0-4 86 0 0 0 86 5-9 86 0 0 0 86 10-14 93 0 0 0 93 15-24 67 34 3 2 106 25-39 6 61 10 12 89 40-59 0 22 17 11 50 60+ 0 7 10 17 34
Table 15: Distribution of the Population Attending School
Nursery Lower Primary
Upper Primary
Lower Secondary
Upper Secondary
University Total
LELAITICH Male 5 33 34 2 1 1 76 Female 10 31 24 1 0 0 66
Lelaitich Male 0 6 5 0 0 0 11 Female 0 2 3 0 0 0 5
Cheptare Male 1 6 4 1 0 0 12 Female 2 4 4 0 0 0 10
Mabutek Male 0 0 4 0 0 0 4 Female 3 3 1 0 0 0 7
Terta Male 0 2 1 0 0 0 3 Female 1 1 6 1 0 0 9
Chepkebit Male 3 3 3 0 0 0 9 Female 3 2 1 0 0 0 6
Kapsasian South
Male 0 5 3 0 0 0 8
Female 0 1 2 0 0 0 3Kapsasian North
Male 0 2 1 0 0 0 3
Female 0 1 1 0 0 0 2Kapkwen Nyak Male
Female Nyakichiwa Male 0 2 2 0 0 0 4
Female 1 4 2 0 0 0 7Sumelei Male 0 0 1 0 0 0 1
Female 0 2 0 0 0 0 2Koita Male 0 0 1 1 0 1 3
Female Kapkwen Lelaitich
Male 1 1 6 0 1 0 9
Female 0 5 1 0 0 0 6Kipsirat Male 0 6 3 0 0 0 9
Female 0 6 2 0 0 0 8Simotwet Male
Female 0 0 1 0 0 0 1KAPSABUL Male 11 35 23 4 3 0 76
Female 12 31 30 2 1 0 76Simotwet Male 1 3 1 0 0 0 5
Female 0 2 1 0 0 0 3Cheboiwo Male 1 3 1 0 0 0 5
Female 1 3 3 0 0 0 7Kapinderem Male 1 1 1 0 0 0 3
Female 1 1 0 0 0 0 2
64
Nursery Lower Primary
Upper Primary
Lower Secondary
Upper Secondary
University Total
Chepkirabach Male 0 1 1 0 0 0 2 Female 0 0 4 0 0 0 4
Cheptebes Male 1 4 3 0 2 0 10 Female 0 5 1 1 0 0 7
Chemengwa Male 1 5 2 1 1 0 10 Female 1 2 5 0 0 0 8
Cheronye Male 1 1 3 0 0 0 5 Female 1 4 3 0 0 0 8
Boreiwek Male 0 1 0 0 0 0 1 Female 2 1 2 0 0 0 5
Chematich Male 1 4 2 1 0 0 8 Female 1 4 1 0 0 0 6
Uswet Male 1 3 3 1 0 0 8 Female 3 4 7 0 1 0 15
Kaptororgo Male 0 1 0 1 0 0 2 Female 0 1 0 0 0 0 1
Kapkoros Male 1 3 1 0 0 0 5 Female 2 0 0 0 0 0 2
Kapsabul Male 1 3 3 0 0 0 7 Female 0 3 2 1 0 0 6
Kiptenden Male 1 2 2 0 0 0 5 Female 0 1 1 0 0 0 2
LUGUMEK Male 7 40 29 1 3 0 80 Female 5 20 18 0 2 0 45
Lugumek Central
Male 1 11 2 0 0 0 14
Female 1 3 2 0 0 0 6Chebitoik Male 0 3 2 0 0 0 5
Female 0 1 0 0 0 0 1Kosia South Male 2 7 3 0 0 0 12
Female 1 2 2 0 1 0 6Kosia North Male 0 4 6 0 0 0 10
Female 0 3 3 0 1 0 7Chebunge Male 1 0 1 0 0 0 2
Female 0 2 1 0 0 0 3Lugumek North
Male 0 0 3 0 0 0 3
Female 0 1 3 0 0 0 4Koita Male 1 6 2 0 1 0 10
Female 1 1 2 0 0 0 4Lugumek West Male 1 2 4 0 0 0 7
Female 0 1 1 0 0 0 2Kapchemoino Male 0 3 2 0 1 0 6
Female 1 2 1 0 0 0 4Chepkoin Male 1 2 2 1 1 0 7
Female 0 3 3 0 0 0 6Kipsirichet Male 0 2 2 0 0 0 4
Female 1 1 0 0 0 0 2TOTAL Male 23 108 86 7 7 1 232
Female 27 82 72 3 3 0 187 Total 50 190 158 10 10 1 419TOTAL (%) Male 9.91 46.55 37.07 3.02 3.02 0.43 100.00
Female 14.44 43.85 38.50 1.60 1.60 0.00 100.00 Total 11.93 45.35 37.71 2.39 2.39 0.24 100.00
65
Table 16: Distribution of the Population Not at School, > 6 years
None Nursery Lower Primary
Upper Primary
Lower Secondary
Upper Secondary
University Total
LELAITICH Male 22 0 11 32 0 13 1 79 Female 47 0 9 31 0 2 0 89
Lelaitich Male 2 0 1 3 0 0 0 6 Female 2 0 1 4 0 0 0 7
Cheptare Male 2 0 5 1 0 1 1 10 Female 8 0 2 1 0 1 0 12
Mabutek Male 2 0 0 1 0 2 0 5 Female 3 0 0 2 0 0 0 5
Terta Male 1 0 0 3 0 2 0 6 Female 4 0 0 2 0 0 0 6
Chepkebit Male 2 0 2 3 0 1 0 8 Female 3 0 0 2 0 0 0 5
Kapsasian South
Male 2 0 0 2 0 0 0 4
Female 2 0 1 1 0 0 0 4Kapsasian North
Male 1 0 0 2 0 0 0 3
Female 3 0 1 3 0 0 0 7Kapkwen Nyak
Male 0 0 0 2 0 1 0 3
Female 1 0 0 2 0 0 0 3Nyakichiwa Male 1 0 1 3 0 2 0 7
Female 5 0 1 2 0 0 0 8Sumelei Male 1 0 0 0 0 0 0 1
Female 2 0 0 1 0 0 0 3Koita Male 1 0 0 0 0 1 0 2
Female 1 0 0 0 0 0 0 1Kapkwen Lela Male 2 0 1 6 0 3 0 12
Female 3 0 1 5 0 0 0 9Kipsirat Male 3 0 1 3 0 0 0 7
Female 5 0 2 3 0 0 0 10Simotwet Male 2 0 0 3 0 0 0 5
Female 5 0 0 3 0 1 0 9KAPSABUL Male 21 0 8 42 4 22 0 97
Female 26 0 6 46 1 4 0 83Simotwet Male 1 0 1 2 0 0 0 4
Female 1 0 0 2 0 1 0 4Cheboiwo Male 3 0 0 4 0 0 0 7
Female 2 0 1 2 0 0 0 5Kapinderem Male 1 0 0 1 0 1 0 3
Female 2 0 0 3 0 0 0 5Chepkirabach Male 3 0 2 3 1 1 0 10
Female 4 0 0 1 0 0 0 5Cheptebes Male 2 0 1 1 0 5 0 9
Female 2 0 0 6 0 1 0 9Chemengwa Male 0 0 1 3 0 2 0 6
Female 1 0 1 2 1 1 0 6Cheronye Male 2 0 0 3 0 0 0 5
Female 1 0 0 2 0 0 0 3Boreiwek Male 1 0 0 5 0 3 0 9
Female 3 0 0 4 0 0 0 7Chematich Male 1 0 1 2 1 1 0 6
Female 1 0 1 3 0 0 0 5Uswet Male 0 0 0 3 1 4 0 8
Female 1 0 0 4 0 1 0 6
66
None Nursery Lower Primary
Upper Primary
Lower Secondary
Upper Secondary
University Total
Kaptororgo Male 3 0 2 3 0 1 0 9 Female 3 0 1 3 0 0 0 7
Kapkoros Male 1 0 0 4 0 2 0 7 Female 4 0 0 3 0 0 0 7
Kapsabul Male 0 0 0 4 1 1 0 6 Female 0 0 1 6 0 0 0 7
Kiptenden Male 3 0 0 4 0 1 0 8 Female 1 0 1 5 0 0 0 7
LUGUMEK Male 31 0 10 37 3 16 0 97 Female 46 1 11 26 1 3 0 88
Lugumek Central
Male 1 0 0 2 1 2 0 6
Female 5 0 2 5 0 0 0 12Chebitoik Male 6 0 2 1 0 2 0 11
Female 2 0 1 2 0 0 0 5Kosia South Male 2 0 1 3 0 3 0 9
Female 3 0 1 3 1 0 0 8Kosia North Male 1 0 1 5 0 2 0 9
Female 5 0 2 1 0 1 0 9Chebunge Male 2 0 0 1 0 2 0 5
Female 6 0 0 2 0 0 0 8Lugumek North
Male 2 0 0 2 0 2 0 6
Female 3 0 0 2 0 0 0 5Koita Male 2 0 2 5 0 0 0 9
Female 3 0 2 0 0 0 0 5Lugumek West
Male 4 0 3 4 1 2 0 14
Female 5 1 2 2 0 2 0 12Kapchemoino Male 3 0 0 3 0 0 0 6
Female 4 0 0 1 0 0 0 5Chepkoin Male 7 0 0 6 1 1 0 15
Female 7 0 1 7 0 0 0 15Kipsirichet Male 1 0 1 5 0 0 0 7
Female 3 0 0 1 0 0 0 4TOTAL Male 74 0 29 111 7 51 1 273
Female 119 1 26 103 2 9 0 260 Total 193 1 55 214 9 60 1 533
TOTAL (%) Male 27.11 0.00 10.62 40.66 2.56 18.68 0.37 100.00 Female 45.77 0.38 10.00 39.62 0.77 3.46 0.00 100.00 Total 36.21 0.19 10.32 40.15 1.69 11.26 0.19 100.00
67
Table 17: Education Profile of the Population, > 6 years
None Nursery Lower primary
Upper primary
Lower secondary
Upper secondary
University Total
LELAITICH Male 22 5 44 66 2 14 2 155 Female 47 7 40 55 1 2 0 152
Lelaitich Male 2 0 7 8 0 0 0 17 Female 2 0 3 7 0 0 0 12
Cheptare Male 2 1 11 5 1 1 1 22 Female 8 1 6 5 0 1 0 21
Mabutek Male 2 0 0 5 0 2 0 9 Female 3 2 3 3 0 0 0 11
Terta Male 1 0 2 4 0 2 0 9 Female 4 1 1 8 1 0 0 15
Chepkebit Male 2 3 5 6 0 1 0 17 Female 3 2 2 3 0 0 0 10
Kapsasian South
Male 2 0 5 5 0 0 0 12
Female 2 0 2 3 0 0 0 7Kapsasian North
Male 1 0 2 3 0 0 0 6
Female 3 0 2 4 0 0 0 9Kapkwen Nyak
Male 0 0 0 2 0 1 0 3
Female 1 0 0 2 0 0 0 3Nyakichiwa Male 1 0 3 5 0 2 0 11
Female 5 1 5 4 0 0 0 15Sumelei Male 1 0 0 1 0 0 0 2
Female 2 0 2 1 0 0 0 5Koita Male 1 0 0 1 1 1 1 5
Female 1 0 0 0 0 0 0 1Kapkwen Lela Male 2 1 2 12 0 4 0 21
Female 3 0 6 6 0 0 0 15Kipsirat Male 3 0 7 6 0 0 0 16
Female 5 0 8 5 0 0 0 18Simotwet Male 2 0 0 3 0 0 0 5
Female 5 0 0 4 0 1 0 10KAPSABUL Male 21 11 43 65 8 25 0 173
Female 26 11 37 76 3 5 0 158Simotwet Male 1 1 4 3 0 0 0 9
Female 1 0 2 3 0 1 0 7Cheboiwo Male 3 1 3 5 0 0 0 12
Female 2 1 4 5 0 0 0 12Kapinderem Male 1 1 1 2 0 1 0 6
Female 2 1 1 3 0 0 0 7Chepkirabach Male 3 0 3 4 1 1 0 12
Female 4 0 0 5 0 0 0 9Cheptebes Male 2 1 5 4 0 7 0 19
Female 2 0 5 7 1 1 0 16Chemengwa Male 0 1 6 5 1 3 0 16
Female 1 1 3 7 1 1 0 14Cheronye Male 2 1 1 6 0 0 0 10
Female 1 1 4 5 0 0 0 11Boreiwek Male 1 0 1 5 0 3 0 10
Female 3 2 1 6 0 0 0 12Chematich Male 1 1 5 4 2 1 0 14
Female 1 1 5 4 0 0 0 11Uswet Male 0 1 3 6 2 4 0 16
Female 1 2 4 11 0 2 0 20
68
None Nursery Lower primary
Upper primary
Lower secondary
Upper secondary
University Total
Kaptororgo Male 3 0 3 3 1 1 0 11 Female 3 0 2 3 0 0 0 8
Kapkoros Male 1 1 3 5 0 2 0 12 Female 4 2 0 3 0 0 0 9
Kapsabul Male 0 1 3 7 1 1 0 13 Female 0 0 4 8 1 0 0 13
Kiptenden Male 3 1 2 6 0 1 0 13 Female 1 0 2 6 0 0 0 9
LUGUMEK Male 31 7 50 66 4 19 0 177 Female 46 6 31 44 1 5 0 133
Lugumek Central
Male 1 1 11 4 1 2 0 20
Female 5 1 5 7 0 0 0 18Chebitoik Male 6 0 5 3 0 2 0 16
Female 2 0 2 2 0 0 0 6Kosia South Male 2 2 8 6 0 3 0 21
Female 3 1 3 5 1 1 0 14Kosia North Male 1 0 5 11 0 2 0 19
Female 5 0 5 4 0 2 0 16Chebunge Male 2 1 0 2 0 2 0 7
Female 6 0 2 3 0 0 0 11Lugumek North
Male 2 0 0 5 0 2 0 9
Female 3 0 1 5 0 0 0 9Koita Male 2 1 8 7 0 1 0 19
Female 3 1 3 2 0 0 0 9Lugumek West
Male 4 1 5 8 1 2 0 21
Female 5 1 3 3 0 2 0 14Kapchemoino Male 3 0 3 5 0 1 0 12
Female 4 1 2 2 0 0 0 9Chepkoin Male 7 1 2 8 2 2 0 22
Female 7 0 4 10 0 0 0 21Kipsirichet Male 1 0 3 7 0 0 0 11
Female 3 1 1 1 0 0 0 6TOTAL Male 74 23 137 197 14 58 2 505
Female 119 24 108 175 5 12 0 443 Total 193 47 245 372 19 70 2 948
TOTAL (%) Male 14.65 4.55 27.13 39.01 2.77 11.49 0.40 100.00 Female 26.86 5.42 24.38 39.50 1.13 2.71 0.00 100.00 Total 20.36 4.96 25.84 39.24 2.00 7.38 0.21 100.00
69
Table 18: Age-Grade Mismatch in the Education Cycle: Lelaitich Location
Nursery Lower Primary Upper Primary Lower Secondary Upper Secondary University TotalMale 0-6 8 5 0 0 0 0 13
7-10 13 69 0 0 0 0 82 11-14 2 34 36 0 0 0 72 15-18 0 0 46 3 2 0 51 19+ 0 0 4 4 5 1 14 Total 23 108 86 7 7 1 232
Female 0-6 9 2 0 0 0 0 11 7-10 14 49 2 0 0 0 65 11-14 0 31 37 0 0 0 68 15-18 0 0 31 1 1 0 33 19+ 0 0 2 2 2 0 6 Total 23 82 72 3 3 0 183
TOTAL 0-6 17 7 0 0 0 0 24 7-10 27 118 2 0 0 0 147 11-14 2 65 73 0 0 0 140 15-18 0 0 77 4 3 0 84 19+ 0 0 6 6 7 1 20 Total 46 190 158 10 10 1 415
% Male 0-6 34.8 4.6 0.0 0.0 0.0 0.0 5.6
7-10 56.5 63.9 0.0 0.0 0.0 0.0 35.3 11-14 8.7 31.5 41.9 0.0 0.0 0.0 31.0 15-18 0.0 0.0 53.5 42.9 28.6 0.0 22.0 19+ 0.0 0.0 4.7 57.1 71.4 100.0 6.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Female 0-6 39.1 2.4 0.0 0.0 0.0 6.0 7-10 60.9 59.8 2.8 0.0 0.0 35.5 11-14 0.0 37.8 51.4 0.0 0.0 37.2 15-18 0.0 0.0 43.1 33.3 33.3 18.0 19+ 0.0 0.0 2.8 66.7 66.7 3.3 Total 100.0 100.0 100.0 100.0 100.0 100.0
TOTAL 0-6 37.0 3.7 0.0 0.0 0.0 0.0 5.8 7-10 58.7 62.1 1.3 0.0 0.0 0.0 35.4 11-14 4.3 34.2 46.2 0.0 0.0 0.0 33.7 15-18 0.0 0.0 48.7 40.0 30.0 0.0 20.2 19+ 0.0 0.0 3.8 60.0 70.0 100.0 4.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Table 19: Primary School Enrolment
Population Net Enrolment
Net enrolment ratio(%)
Gross Enrolment
Gross enrolment ratio(%)
Lelaitich Male 53 47 88.7 67 126.4 Female 53 50 94.3 55 103.8 Total 106 97 91.5 122 115.1
Kapsabul Male 51 47 92.2 58 113.7 Female 51 49 96.1 61 119.6 Total 102 96 94.1 119 116.7
Lugumek Male 67 58 86.6 69 103.0 Female 41 34 82.9 38 92.7 Total 108 92 85.2 107 99.1
Total Male 171 152 88.9 194 113.5 Female 145 133 91.7 154 106.2 Total 316 285 90.2 348 110.1
70
Table 20: Literacy Status of the Non-school Population, > 8 years
Can read Can’t read Can write Can’t write Can read/write TotalLelaitich Male 56 17 55 18 55 73
Female 35 48 35 48 35 83 Total 91 65 90 66 90 156
Kapsabul Male 70 21 70 21 70 91 Female 48 32 47 33 47 80 Total 118 53 117 54 117 171
Lugumek Male 61 26 61 26 61 87 Female 36 48 35 49 35 84 Total 97 74 96 75 96 171
TOTAL Male 187 64 186 65 186 251 Female 119 128 117 130 117 247 Total 306 192 303 195 303 498
PERCENT Lelaitich Male 76.7 23.3 75.3 24.7 75.3 100.0
Female 42.2 57.8 42.2 57.8 42.2 100.0 Total 58.3 41.7 57.7 42.3 57.7 100.0
Kapsabul Male 76.9 23.1 76.9 23.1 76.9 100.0 Female 60.0 40.0 58.8 41.3 58.8 100.0 Total 69.0 31.0 68.4 31.6 68.4 100.0
Lugumek Male 70.1 29.9 70.1 29.9 70.1 100.0 Female 42.9 57.1 41.7 58.3 41.7 100.0 Total 56.7 43.3 56.1 43.9 56.1 100.0
TOTAL Male 74.5 25.5 74.1 25.9 74.1 100.0 Female 48.2 51.8 47.4 52.6 47.4 100.0 Total 61.4 38.6 60.8 39.2 60.8 100.0
Table 21: Reasons for Dropping Out of Primary School for Period 1993-1996
Pregnancy Marriage Fees Failed exam
Other Total Enrolment Dropout rate (%)
Lelaitich Male 0 0 8 2 1 11 79 13.9 Female 0 1 2 2 1 6 62 9.7 Total 0 1 10 4 2 17 141 12.1
Kapsabul Male 0 0 13 1 1 16 74 21.6 Female 1 10 6 1 0 19 80 23.8 Total 1 10 19 2 1 35 154 22.7
Lugumek Male 0 1 8 1 8 19 89 21.3 Female 1 8 1 0 3 13 51 25.5 Total 1 9 9 1 11 32 140 22.9
TOTAL Male 0 1 29 4 10 46 242 19.0 Female 2 19 9 3 4 38 193 19.7 Total 2 20 38 7 14 84 435 19.3
TOTAL (%)
Male 0.0 2.2 63.0 8.7 21.7 100.0
Female 5.3 50.0 23.7 7.9 10.5 100.0 Total 2.4 23.8 45.2 8.3 16.7 100.0
71
Table 22: Distribution of the Population by Place of Birth Within Location Bomet District Outside District Total
Lelaitich Male 177 4 6 187 Female 159 21 5 185 Total 336 25 11 372
Kapsabul Male 196 11 1 208 Female 159 22 11 192 Total 355 33 12 400
Lugumek Male 203 8 3 214 Female 142 21 4 167 Total 345 29 7 381
TOTAL Male 576 23 10 609 Female 460 64 20 544 Total 1,036 87 30 1,153
PERCENT Lelaitich Male 94.7 2.1 3.2 100.0
Female 85.9 11.4 2.7 100.0 Total 90.3 6.7 3.0 100.0
Kapsabul Male 94.2 5.3 0.5 100.0 Female 82.8 11.5 5.7 100.0 Total 88.8 8.3 3.0 100.0
Lugumek Male 94.9 3.7 1.4 100.0 Female 85.0 12.6 2.4 100.0 Total 90.6 7.6 1.8 100.0
TOTAL Male 94.6 3.8 1.6 100.0 Female 84.6 11.8 3.7 100.0 Total 89.9 7.5 2.6 100.0
Table 23: Distribution of Group Membership by Type of Self-Help Group (15+ years)
Merry-go-round (cash)
Labor Livestock Bee-keeping
Posho mill
Shop ‘Nyayo’ Other Total
Lelaitich Male 6 8 0 1 0 1 3 0 19 Female 22 17 1 0 0 0 4 1 45 Total 28 25 1 1 0 1 7 1 64
Kapsabul Male 0 1 2 0 0 0 5 0 8 Female 7 6 0 0 0 2 19 0 34 Total 7 7 2 0 0 2 24 0 42
Lugumek Male 5 0 0 1 1 5 12 1 25 Female 7 7 0 0 2 4 29 0 49 Total 12 7 0 1 3 9 41 1 74
TOTAL Male 11 9 2 2 1 6 20 1 52 Female 36 30 1 0 2 6 52 1 128 Total 47 39 3 2 3 12 72 2 180
PERCENT Lelaitich Male 31.6 42.1 0.0 5.3 0.0 5.3 15.8 0.0 100.0
Female 48.9 37.8 2.2 0.0 0.0 0.0 8.9 2.2 100.0 Total 43.8 39.1 1.6 1.6 0.0 1.6 10.9 1.6 100.0
Kapsabul Male 0.0 12.5 25.0 0.0 0.0 0.0 62.5 0.0 100.0 Female 20.6 17.6 0.0 0.0 0.0 5.9 55.9 0.0 100.0 Total 16.7 16.7 4.8 0.0 0.0 4.8 57.1 0.0 100.0
Lugumek Male 20.0 0.0 0.0 4.0 4.0 20.0 48.0 4.0 100.0 Female 14.3 14.3 0.0 0.0 4.1 8.2 59.2 0.0 100.0 Total 16.2 9.5 0.0 1.4 4.1 12.2 55.4 1.4 100.0
TOTAL Male 21.2 17.3 3.8 3.8 1.9 11.5 38.5 1.9 100.0 Female 28.1 23.4 0.8 0.0 1.6 4.7 40.6 0.8 100.0 Total 26.1 21.7 1.7 1.1 1.7 6.7 40.0 1.1 100.0
72
Table 24: Types of Sickness in the Preceding Two Weeks by Age
Vomit/ diarrhea
Malaria/ fever
Cough/ cold
Injury/ burns
Other Total sick
Total sample
% sick
0-5 years 3 4 31 2 1 41 204 20.106-15 years 3 4 29 2 5 43 399 10.7816 and over 4 20 24 6 10 64 548 11.68Total 10 28 84 10 16 148 1,151 12.86PERCENT 6.8 18.9 56.8 6.8 10.8 100.0
Types of Sickness by First action taken Nothing/prayers 0 4 29 2 3 38 25.7 Traditional healer
2 3 5 0 2 12 8.1
OTC drugs 5 12 30 4 2 53 35.8 Health facility 3 9 20 4 9 45 30.4 Total 10 28 84 10 16 148 100.0 Table 25: Number of Disabilities in the Responding Population
Seeing Hearing Speaking Arms Legs Hunch Mental Total Disabilities
Total Sample
%
Male 3 4 2 3 5 0 2 15 609 2.46Female 3 1 1 1 2 0 2 9 544 1.65Total 6 5 3 4 7 0 4 24 1,153 2.08 Table 26: Distribution of Under-Fives by Place of Delivery
Number PERCENT Hospital/ health facility Home Total Hospital/ health facility Home Total
Lelaitich 14 38 52 26.9 73.1 100.0Kapsabul 19 41 60 31.7 68.3 100.0Lugumek 12 48 62 19.4 77.4 100.0TOTAL 45 127 174 25.9 73.0 100.0 Table 27: Distribution of Under-Fives by Delivering Personnel
Doctor Nurse/ midwife TBA Self Total Lelaitich 7 3 7 29 52Kapsabul 12 6 12 16 60Lugumek 4 9 36 6 62TOTAL 23 18 55 51 174PERCENT 13.2 10.3 31.6 29.3 100.0 Table 28: Immunization Status by Sex, 11-59 Months
Card BCG BCG Scar
Polio B
Polio 1
Polio 2
Polio 3
DPT 1
DPT 2
DPT 3
Measles Full immu.
Total
Male 67 71 66 70 71 71 68 71 71 68 66 65 71Female 67 68 68 68 68 66 65 67 67 65 64 64 68Total 134 139 134 138 139 137 133 138 138 133 130 129 139PERCENT Male 94.4 100.0 93.0 98.60 100.0 100.0 95.8 100.0 100.0 95.8 93.0 91.5 Female 98.5 100.0 100.0 100.0 100.0 97.1 95.6 98.5 98.5 95.6 94.1 94.1 Total 96.4 100.0 96.4 99.3 100.0 98.6 95.7 99.3 99.3 95.7 93.5 92.8
73
Table 29: Distribution of Under-Fives by Months Breastfed 0-12 months 13-24 months >24 months Exclusive Months Breastfed Total
Still Breastfeeding 40 33 3 3.7 12.6 76Stopped Breastfeeding 20 73 5 4.0 18.2 98PERCENT Still Breastfeeding 52.6 43.4 3.9 Stopped Breastfeeding 20.4 74.5 5.1 Table 30: Distribution of Under-Fives by Type of First Supplement
Milk other than breast Porridge Semi-solids Other Total Still Breastfeeding 37 28 5 6 76Stopped Breastfeeding 57 35 5 1 98PERCENT Still Breastfeeding 48.7 36.8 6.6 7.9 100.0Stopped Breastfeeding 58.2 35.7 5.1 1.0 100.0 Table 31: Construction Materials of the Main residential Structure
Wall Floor Roof Mud/ earth Timber Mud/ earth Cement Grass Iron sheets
Lelaitich 63 0 63 0 49 14Kapsabul 66 2 66 2 44 24Lugumek 65 1 66 0 49 17TOTAL 194 3 195 2 142 55PERCENT Lelaitich 100.0 0.0 100.0 0.0 77.8 22.2Kapsabul 97.1 2.9 97.1 2.9 64.7 35.3Lugumek 98.5 1.5 100.0 0.0 74.2 25.8TOTAL 98.5 1.5 99.0 1.0 72.1 27.9 Table 32: Combination of Construction Materials of the Main residential Structure Wall Mud/earth Timber
194 3
Roof Grass Iron sheets Grass Iron sheets 142 52 0 3
Floor Mud/earth Cement Mud/earth Cement Mud/earth Cement Mud/earth Cement 142 0 51 1 0 0 2 1
Table 33: Distribution of Households by Ventilation and Human-Animal Interaction
Main house
windows
Kitchen windows
Main house:
human and livestock
Main house
without livestock
Separate kitchen (Yes)
Kitchen: human
and livestock
Main house and kitchen: human and livestock
Total
Lelaitich 1.9 0.4 23 40 18 7 27 63Kapsabul 2.2 0.8 22 46 30 6 32 68Lugumek 2.1 0.6 29 37 21 4 36 66TOTAL 2.1 0.6 74 123 69 17 95 197PERCENT Lelaitich 36.5 63.5 28.6 38.9 42.9 100.0Kapsabul 32.4 67.6 44.1 20.0 47.1 100.0Lugumek 43.9 56.1 31.8 19.0 54.5 100.0TOTAL 37.6 62.4 35.0 24.6 48.2 100.0
74
Table 34: Distribution of Households by Source of Water and Mean Distance to Source
Water source: Wet season Water source: Dry season Mean distance to source(km)
Shallow well
Roof Pond/ dam
River Shallow well
Roof Pond/dam
River Wet Dry
Lelaitich 0 13 43 10 0 0 57 0.26 4.44Kapsabul 2 14 30 23 0 0 68 0.63 2.83Lugumek 1 6 9 51 0 0 66 1.45 2.01TOTAL 3 33 82 84 0 0 191 0.79 3.07 Table 35: Distribution of Households by Distance to Water Sources (km)
Wet Dry 0-4 4-7 7-10 >10 0-4 4-7 7-10 >10
Lelaitich 63 0 0 0 26 29 8 0Kapsabul 68 0 0 0 43 19 6 0Lugumek 64 2 0 0 64 2 0 0TOTAL 195 2 0 0 133 50 14 0 Table 36: Distribution of Households by Household Members Mainly Responsible for Collecting Water
Who collects water 20-litre containers
Water treatment
Wife/ female children
Husband/ male children
Other Don’t boil
Boil Total
Lelaitich 59 2 2 2.37 59 4 63Kapsabul 64 4 0 2.62 64 4 68Lugumek 65 1 0 2.05 56 10 66TOTAL 188 7 2 2.35 179 18 197TOTAL (%)
95.4 3.6 1.0 90.9 9.1 100.0
Table 37: Distribution of Households by Disposal of Rubbish and Human Excreta
Toilet Rubbish disposal Own pit Neighbor’s pit Bush Burning Other Total
Lelaitich 25 9 29 47 16 63Kapsabul 29 2 37 66 2 68Lugumek 21 2 43 51 15 66TOTAL 75 13 109 164 33 197PERCENT Lelaitich 39.7 14.3 46.0 74.6 25.4 100.0Kapsabul 42.6 2.9 54.4 97.1 2.9 100.0Lugumek 31.8 3.0 65.2 77.3 22.7 100.0TOTAL 38.1 6.6 55.3 83.2 16.8 100.0 Table 38: Distribution of Households by Sources of Cooking and Lighting Fuels
Cooking Fuel Lighting Fuel Total Firewood Other Paraffin Other
Lelaitich 63 0 61 2 63Kapsabul 68 0 66 2 68Lugumek 66 0 64 2 66TOTAL 197 0 191 6 197PERCENT Lelaitich 100.0 0.0 96.8 3.2 100.0Kapsabul 100.0 0.0 97.1 2.9 100.0Lugumek 100.0 0.0 97.0 3.0 100.0TOTAL 100.0 0.0 97.0 3.0 100.0
75
Table 39: Distribution of Households by Whether Own Selected Assets
Bicycle Car Radio Plough Total Lelaitich 14 0 20 17 63Kapsabul 15 1 28 25 68Lugumek 24 0 34 33 66TOTAL 53 1 82 75 197PERCENT Lelaitich 22.2 0.0 31.7 27.0 100.0Kapsabul 22.1 1.5 41.2 36.8 100.0Lugumek 36.4 0.0 51.5 50.0 100.0TOTAL 26.9 0.5 41.6 38.1 100.0 Table 40: Distribution of Households by Distance to Amenities (km)
Market Primary school Secondary school Hospital Lelaitich 4.08 1.20 5.18 4.81Kapsabul 3.87 1.42 9.46 2.48Lugumek 2.40 1.39 7.47 4.69TOTAL 3.44 1.34 7.42 3.97 Table 41A: Crop Production Costs per household: Lelaitich Sub-location (Shs)
Maize Millet Sorghum Beans Sweet potatoes
Total Total(%)
Short rains
Long rains
Short rains
Long rains
Short rains
Long rains
Short rains
Long rains
Short rains
Long rains
Planted area (acres) 0.71 1.32 0.02 0.04 0.02 0.07 0.26 0.49 0.03 0.16 AVOIDABLE COSTS
Certified seeds (Shs) 314.6 611.3 0.0 0.0 0.0 0.0 0.0 5.7 0.0 0.0 931.7 51.2Uncertified seeds (Shs)
20.9 27.5 0.8 5.5 1.7 8.8 28.7 80.1 0.6 10.5 185 10.2
Fertilizer (Shs) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0Land preparation/ planting (Shs)
165.9 322.1 0.0 0.0 7.9 0.0 0.0 6.3 0.0 1.6 503.8 27.7
Weeding/harvesting 23.8 34.6 0.0 0 0.0 0.0 0.0 0.0 0.0 0.0 58.4 3.2Land lease/rent 57.1 23.8 0.0 7.9 7.9 0.0 0.0 0.0 0.0 0.0 96.8 5.3Agricultural implements
24.1 20.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 44.8 2.5
Total costs 606.4 1,040.0 0.8 13.4 17.5 8.8 28.7 92.1 0.6 12.1 1,820.50 100.0 Table 41B: Crop Production Costs per household: Kapsabul Sub-location (Shs)
Maize Millet Sorghum Beans Sweet potatoes
Total Total (%)
Short rains
Long rains
Shortrains
Longrains
Shortrains
Longrains
Shortrains
Longrains
Shortrains
Long rains
Planted area (acres) 0.57 1.03 0.00 0.00 0.04 0.00 0.14 0.36 0.03 0.11 AVOIDABLE COSTS
Certified seeds (Shs) 298.7 679.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 978.4 55.1Uncertified seeds (Shs)
5.6 1.8 0.0 0.0 0.0 0.0 14.7 33.8 0.0 0.9 56.8 3.2
Fertilizer (Shs) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0..0 0.0 0.0 0.0 0.0Land preparation/ planting (Shs)
76.5 307.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 383.8 21.6
Weeding/harvesting 35.3 97.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 132.4 7.5Land lease/rent 29.4 102.9 0.0 0.0 0.0 0.0 0.0 29.4 0.0 0.0 161.8 9.1Agricultural implements
5.4 55.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 61.2 3.4
Total costs 450.9 1,244.6 0.0 0.0 0.0 0.0 14.7 63.2 0.0 0.9 1,774.3 100.0
76
Table 41C: Crop Production Costs per household: Lugumek Sub-location (Shs)
Maize Millet Sorghum Beans Sweet potatoes
Total Total(%)
Short rains
Long rains
Shortrains
Longrains
Shortrains
Longrains
Shortrains
Longrains
Shortrains
Long rains
Planted area (acres) 0.09 2.58 0.00 0.09 0.00 0.05 0.06 0.48 0.01 0.05 AVOIDABLE COSTS
Certified seeds (Shs) 53.0 1,590.9 0.0 0.0 0.0 0 0.0 0.0 0.0 0.0 1,643.9 51.8Uncertified seeds (Shs)
0.0 28.0 0.0 1.1 0.0 1.8 18.5 73.1 0.0 0.0 122.5 3.9
Fertilizer (Shs) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 15.2 0.0 0.0 15.2 0.5Land preparation/ planting (Shs)
35.5 748.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 783.8 24.7
Weeding/harvesting 16.7 337.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 354.2 11.2Land lease/rent 0.0 223.50 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 223.5 7.0Agricultural implements
2.3 27.90 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 30.2 1.0
Total costs 107.4 2,956.20 0.0 1.1 0.0 1.8 18.5 88.3 0.0 0.0 3,173.2 100.0 Table 41D: Crop Production Costs per household: Lelaitich Location (Shs)
Maize Millet Sorghum Beans Sweet potatoes
Total Total(%)
Short rains
Long rains
Short rains
Long rains
Short rains
Long rains
Short rains
Long rains
Short rains
Long rains
Planted area (acres) 0.45 1.64 0.01 0.05 0.02 0.04 0.15 0.44 0.02 0.11 AVOIDABLE COSTS
Certified seeds (Shs) 221.5 963.1 0.0 0.0 0.0 0.0 0.0 1.8 0.0 0.0 1,186.4 52.5Uncertified seeds (Shs)
8.6 18.8 0.3 2.1 0.5 3.4 20.4 61.8 0.2 3.7 119.8 5.3
Fertilizer (Shs) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.1 0.0 0.0 5.1 0.2Land preparation/ planting (Shs)
91.3 459.8 0.0 0.0 2.5 0.0 0.0 2.0 0.0 0.5 556.2 24.6
Weeding/harvesting 25.4 157.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 183.0 8.1Land lease/rent 28.4 118.0 0.0 2.5 2.5 0.0 0.0 10.2 0.0 0.0 161.7 7.2Agricultural implements
10.4 35.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 45.5 2.0
Total costs 385.6 1,752.6 0.3 4.6 5.6 3.4 20.4 80.9 0.2 4.2 2,257.7 100.0 Table 42A: Crop Production per Household: Lelaitich Sub-location
Maize Millet Sorghum Beans Sweet potatoes Short
rains Long rains
Short rains
Long rains
Short rains
Long rains
Short rains
Long rains
Short rains
Long rains
Harvest (kg) 46.30 168.81 0.79 1.83 0.44 4.44 1.65 5.81 33.62 20.68Sales (Shs) 0.00 61.43 0.00 3.17 0.00 0.00 7.14 0.00 0.00 0.00Gifts out (kg) 4.10 8.87 0.00 0.10 0.00 0.57 0.00 0.02 13.51 1.03Retention for seeds (kg)
0.29 1.02 0.03 0.03 0.00 0.05 0.03 0.06 0.00 0.00
Home consumption (kg)
40.49 139.40 0.73 1.57 0.44 3.13 1.51 5.73 20.11 19.41
In store (kg) 1.43 15.16 0.00 0.00 0.00 0.70 0.00 0.00 0.00 0.00Planted area (acres)
0.71 1.32 0.02 0.04 0.02 0.07 0.26 0.49 0.03 0.16
Output (kg) per acre
65.0 127.8 34.5 42.6 20.7 61.2 6.3 11.8 1,033.2 129.3
77
Table 42B: Crop Production per Household: Kapsabul Sub-location
Maize Millet Sorghum Beans Sweet Potatoes Short
rains Long rains
Short rains
Long rains
Short rains
Long rains
Short rains
Long rains
Short rains
Long rains
Harvest (kg) 98.31 185.59 0.00 0.29 0.00 0.00 1.09 4.63 6.32 11.13Sales (Shs) 79.41 39.71 0.00 0.00 0.00 0.00 0.37 44.12 0.00 0.00Gifts out (kg) 0.35 2.50 0.00 0.00 0.00 0.00 0.06 0.00 0.00 0.15Retention for seeds (kg)
0.65 0.21 0.00 0.00 0.00 0.00 0.01 0.06 0.37 0.00
Home consumption (kg)
74.51 137.51 0.00 0.29 0.00 0.00 0.91 3.10 5.96 10.98
In store (kg) 14.56 40.66 0.00 0.00 0.00 0.00 0.09 0.00 0.00 0.00Planted area (acres)
0.57 1.03 0.00 0.00 0.04 0.00 0.14 0.36 0.03 0.11
Output (kg) per acre
173.6 180.3 80.0 0.0 7.6 13.0 226.3 100.2
Table 42C: Crop Production per Household: Lugumek Sub-location
Maize Millet Sorghum Beans Sweet potatoes Short
rains Long rains
Short rains
Long rains
Short rains
Long rains
Short rains
Long rains
Short rains
Long rains
Harvest (kg) 25.91 540.05 0.00 7.76 0.00 2.79 1.53 4.06 0.00 3.48Sales (Shs) 63.64 1387.27 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00Gifts out (kg) 0.00 7.38 0.00 0.00 0.00 0.00 0.00 0.03 0.00 0.00Retention for seeds (kg)
0.00 0.15 0.00 0.03 0.00 0.08 0.27 0.08 0.00 0.00
Home consumption (kg)
13.48 208.55 0.00 7.35 0.00 2.33 1.26 3.50 0.00 3.48
In store (kg) 6.97 220.98 0.00 0.38 0.00 0.91 0.00 0.42 0.00 0.00Planted area (acres)
0.09 2.58 0.00 0.09 0.00 0.05 0.06 0.48 0.01 0.05
Output (kg) per acre
285.0 209.7 84.6 59.4 25.3 8.4 0.0 65.7
78
Table 42D: Crop Production per Household: Lelaitich Location
Maize Millet Sorghum Beans Sweet potatoes Short
rains Long rains
Short rains
Long rains
Short rains
Long rains
Short rains
Long rains
Short rains
Long rains
Harvest (kg) 57.42 298.97 0.25 3.28 0.14 2.36 1.42 4.82 12.93 11.62Sales (Shs) 48.73 498.12 0.00 1.02 0.00 0.00 2.41 15.23 0.00 0.00Gifts out (kg) 1.43 6.17 0.00 0.03 0.00 0.18 0.02 0.02 4.32 0.38Retention for seeds (kg)
0.31 0.45 0.01 0.02 0.00 0.04 0.11 0.07 0.13 0.00
Home consumption (kg)
43.19 161.91 0.23 3.07 0.14 1.78 1.22 4.08 8.49 11.16
In store (kg) 7.82 92.92 0.00 0.13 0.00 0.53 0.03 0.14 0.00 0.00Planted area (acres)
0.45 1.64 0.01 0.05 0.02 0.04 0.15 0.44 0.02 0.11
Output (kg) per acre
126.6 182.2 34.5 71.9 7.3 60.5 9.2 10.9 572.6 108.4
Memorandum Items:
Total planted area (acres):
Lelaitich 351 694 10 20 9 35 123 251 15 79Kapsabul 288 539 0 2 33 0 73 189 17 72Lugumek 45 1,238 0 42 0 21 31 225 4 25Total 684 2,472 10 65 42 56 227 665 35 177
Total production (kgs):
Lelaitich 23,269 83,948 350 803 196 2,119 728 2,700 15,253 9,178Kapsabul 51,851 98,058 0 144 0 0 575 2,298 3,149 6,742Lugumek 12,757 265,592 0 3,593 0 1,327 780 1,950 0 1,693Total 87,876 447,598 350 4,540 196 3,445 2,083 6,947 18,402 17,613 Table 43: Distribution of Households by Farm Management Practices
Maize Beans Lelaitich Kapsabul Lugumek Total Lelaitich Kapsabul Lugumek Total
LAND PREPARATION Wife and female children 14 3 11 28 7 1 1 9Husband and male children 34 32 48 114 15 7 17 39Hired Labor 10 8 2 20 3 2 0 5Total 58 43 61 162 25 10 18 53
PLANTING Wife and female children 31 6 14 51 16 1 2 19Husband and male children 23 32 46 101 8 8 16 32Hired Labor 4 5 0 9 1 1 0 2Total 58 43 60 161 25 10 18 53
WEEDING Wife and female children 53 40 58 151 22 9 18 49Husband and male children 1 1 2 4 1 0 0 1Hired Labor 2 1 1 4 1 1 0 2Total 56 42 61 159 24 10 18 52
HARVESTING Wife and female children 42 27 54 123 21 7 18 46Husband and male children 11 15 7 33 4 2 0 6
79
Maize Beans Lelaitich Kapsabul Lugumek Total Lelaitich Kapsabul Lugumek Total
Hired Labor 0 0 0 0 0 0 0 0Total 53 42 61 156 25 9 18 52 LAND PREPARATION METHOD
Burning 2 0 0 2 Burning and digging/ ploughing
2 0 0 2
Digging/ ploughing 56 43 63 162 Total 60 43 63 166 LAND PREPARATION IMPLEMENT
Tractor 9 3 9 21 Plough 39 40 53 132 Hand-hoe 11 1 1 13 Total 59 44 63 166 0 PLANTING METHOD 0 Broadcasting 3 5 4 12 Line planting 56 40 59 155 Total 59 45 63 167 PERCENT LAND PREPARATION Wife and female children 24.1 7.0 18.0 17.3 28.0 10.0 5.6 17.0Husband and male children 58.6 74.4 78.7 70.4 60.0 70.0 94.4 73.6Hired Labor 17.2 18.6 3.3 12.3 12.0 20.0 0.0 9.4Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 PLANTING Wife and female children 53.4 14.0 23.3 31.7 64.0 10.0 11.1 35.8Husband and male children 39.7 74.4 76.7 62.7 32.0 80.0 88.9 60.4Hired Labor 6.9 11.6 0.0 5.6 4.0 10.0 0.0 3.8Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 WEEDING Wife and female children 94.6 95.2 95.1 95.0 91.7 90.0 100.0 94.2Husband and male children 1.8 2.4 3.3 2.5 4.2 0.0 0 1.9Hired Labor 3.6 2.4 1.6 2.5 4.2 10.0 0 3.8Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 HARVESTING Wife and female children 79.2 64.3 88.5 78.8 84.0 77.8 100.0 88.5Husband and male children 20.8 35.7 11.5 21.2 16.0 22.2 0.0 11.5Hired Labor 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 LAND PREPARATION METHOD
Burning 3.3 0.0 0.0 1.2 Burning and digging/ ploughing
3.3 0.0 0.0 1.2
Digging/ ploughing 93.3 100.0 100.0 97.6 Total 100.0 100.0 100.0 100.0 LAND PREPARATION
80
Maize Beans Lelaitich Kapsabul Lugumek Total Lelaitich Kapsabul Lugumek Total
IMPLEMENT Tractor 15.3 6.8 14.3 12.7 Plough 66.1 90.9 84.1 79.5 Hand-hoe 18.6 2.3 1.6 7.8 Total 100.0 100.0 100.0 100 PLANTING METHOD Broadcasting 5.1 11.1 6.3 7.2 Line planting 94.9 88.9 93.7 92.8 Total 100.0 100.0 100.0 100.0 Table 44A: Livestock Production and Disposal per Household: Lelaitich sub-location
Cattle Goats Sheep Chicken DonkeysNumber, December 1996 4.00 1.62 1.08 7.86 0.41Number bought 0.29 0.21 0.06 0.56 0.06Number born 1.06 0.79 0.41 8.51 0.06Gifts in 0.11 0.00 0.02 0.00 0.00Number sold 0.73 0.48 0.22 4.08 0.11Home consumption 0.10 0.14 0.06 0.78 0.00Number dead 0.65 0.16 0.32 2.94 0.00Gifts out 0.06 0.00 0.00 0.22 0.00Number, December 1997 3.92 1.84 0.97 8.90 0.43Livestock sales (Shs) 4034.92 393.02 157.14 397.46 88.89Milk production (litres) 276.67 11.02 Egg production (number) 296.67 Table 44B: Livestock Production and Disposal per Household: Kapsabul sub-location
Cattle Goats Sheep Chicken Donkeys Number, December 1996 4.75 2.49 0.87 6.69 0.74Number bought 0.18 0.15 0.13 0.65 0.09Number born 1.28 0.94 0.32 6.16 0.16Gifts in 0.71 0.12 0.03 0.00 0.00Number sold 1.03 0.29 0.10 1.60 0.07Home consumption 0.07 0.09 0.01 0.93 0.00Number dead 0.50 0.10 0.15 2.13 0.00Gifts out 0.16 0.04 0.06 0.00 0.01Number, December 1997 5.15 3.16 1.03 8.84 0.90Livestock sales (Shs) 6247.06 254.41 85.29 163.38 64.71Milk production (litres) 452.65 5.29 Egg production (number) 159.62 Table 44C: Livestock Production and Disposal per Household: Lugumek sub-location
Cattle Goats Sheep Chicken Donkeys Number, December 1996 7.12 5.26 1.55 10.47 0.65Number bought 0.23 0.18 0.05 0.17 0.05Number born 2.06 1.76 0.55 13.24 0.21Gifts in 0.30 0.20 0.14 0.14 0.03Number sold 1.08 0.95 0.30 5.70 0.02Home consumption 0.09 0.08 0.00 0.86 0.00Number dead 1.03 0.62 0.20 5.73 0.05Gifts out 0.27 0.11 0.00 0.05 0.05Number, December 1997 7.24 5.64 1.77 11.68 0.83Livestock sales (Shs) 6272.73 903.79 236.36 584.09 22.73Milk production (litres) 373.14 0.00 Egg production (number) 269.59
81
Table 44D: Livestock Production and Disposal per Household: Lelaitich Location
Cattle Goats Sheep Chicken Donkeys Number, December 1996 5.30 3.14 1.16 8.33 0.60Number bought 0.23 0.18 0.08 0.46 0.07Number born 1.47 1.17 0.43 9.28 0.15Gifts in 0.38 0.11 0.06 0.05 0.01Number sold 0.95 0.57 0.21 3.77 0.07Home consumption 0.09 0.10 0.03 0.86 0.00Number dead 0.73 0.29 0.22 3.59 0.02Gifts out 0.17 0.05 0.02 0.09 0.02Number, December 1997 5.46 3.57 1.26 9.81 0.73Livestock sales (Shs) 5548.22 516.29 158.88 379.19 58.38Milk production (litres) 369.73 5.35 Egg production (number) 240.29
Total livestock (1997) Lelaitich 1,866 927 500 5,028 215Kapsabul 2,608 1,563 497 4,888 482Lugumek 3,471 2,668 881 5,628 398Total 7,945 5,158 1,878 15,544 1,095 Table 45A: Livestock Production Costs per Household: Lelaitich sub-location (Shs)
Cattle Goats Sheep Chicken Donkeys Total Total (%) Dipping 565.4 28.7 15.5 0.0 0.0 609.6 42.5Commercial feeds/mineral supplement
249.5 22.9 6.2 158.7 0.0 437.2 30.5
Vaccination/drugs/vet services 223.8 12.2 10.9 0.0 0.0 246.9 17.2Hired labour 61.9 0.0 0.0 0.0 0.0 61.9 4.3Land lease/rent 78.6 0.0 0.0 0.0 0.0 78.6 5.5Other costs 0.0 0.0 0.0 0.3 0.0 0.3 0.0Total costs 1,179.2 63.8 32.5 159.0 0.0 1,434.5 100.0 Table 45B: Livestock Production Costs per Household: Kapsabul sub-location (Shs)
Cattle Goats Sheep Chicken Donkeys Total Total (%) Dipping 160.3 0.3 0.3 0.0 0.0 160.8 16.2Commercial feeds/mineral supplement
23.9 0.0 0.0 0.0 0.0 23.9 2.4
Vaccination/drugs/vet services 362.5 7.5 2.6 0.0 0.0 372.6 37.5Hired labour 367.6 0.0 0.0 0.0 0.0 367.6 37.0Land lease/rent 57.4 0.0 0.0 0.0 0.0 57.4 5.8Other costs 11.8 0.0 0.0 0.0 0.0 11.8 1.2Total costs 983.4 7.8 2.9 0.0 0.0 994.1 100.0 Table 45C: Livestock Production Costs per Household: Lugumek sub-location (Shs)
Cattle Goats Sheep Chicken Donkeys Total Total (%) Dipping 474.4 78.7 16.7 0.0 0.0 569.8 42.4Commercial feeds/mineral supplement
53.8 0.6 0.0 0.0 0.0 54.4 4.0
Vaccination/drugs/vet services 449.8 36.9 9.5 0.0 0.8 497.0 36.9Hired labour 196.7 0.0 0.0 0.0 0.0 196.7 14.6Land lease/rent 27.3 0.0 0.0 0.0 0.0 27.3 2.0Other costs 0.0 0.0 0.0 0.0 0.0 0.0 0.0Total costs 1,202.0 116.2 26.2 0.0 0.8 1,345.1 100.0
82
Table 45D: Livestock Production Costs per Household: Lelaitich Location (Shs)
Cattle Goats Sheep Chicken Donkeys Total Total (%)Dipping 395.1 35.6 10.6 0.0 0.0 441.4 35.2Commercial feeds/mineral supplement 106.1 7.5 2.0 50.8 0.0 166.3 13.3Vaccination/drugs/vet services 347.4 18.9 7.6 0.0 0.3 374.1 29.9Hired labour 212.6 0.0 0.0 0.0 0.0 212.6 17.0Land lease/rent 54.1 0.0 0.0 0.0 0.0 54.1 4.3Other costs 4.1 0.0 0.0 0.1 0.0 4.2 0.3Total costs 1,119.2 62.0 20.2 50.9 0.3 1,252.5 100.0 Table 46: Household Income by Sub-location (Shs)
Shs PERCENT Lelaitich Kapsabul Lugumek Total Lelaitich Kapsabul Lugumek Total
Wage income 11,971 16,994 12,900 14,016 44.7 50.3 34.7 42.9Self employment 5,508 2,965 6,045 4,810 20.6 8.8 16.3 14.7Lease/rental income 8 134 64 70 0.0 0.4 0.2 0.2Transfers in 193 188 91 157 0.7 0.6 0.2 0.5Transfers out 123 162 15 100 0.5 0.5 0.0 0.3Crop income 3,162 4,293 8,584 5,369 11.8 12.7 23.1 16.4Livestock income 6,076 9,354 9,512 8,358 22.7 27.7 25.6 25.6Annual income 26,794 33,765 37,180 32,680 100.0 100.0 100.0 100.0Monthly income 2,233 2,814 3,098 2,723 Household size 5.90 5.88 5.77 5.85 Paid employees 17 18 17 52 32.7 34.6 32.7 100.0Self-employed 16 8 48 72 22.2 11.1 66.7 100.0 Table 47: Income per capita by Sub-location (Shs)
Shs PERCENT Lelaitich Kapsabul Lugumek Total Lelaitich Kapsabul Lugumek Total
Wage income 1,970 2,401 2,705 2,365 36.6 43.3 36.5 38.6Self employment 980 491 1,192 882 18.2 8.8 16.1 14.4Lease/rental income 1 16 48 22 0.0 0.3 0.6 0.4Transfers in 56 39 18 37 1.0 0.7 0.2 0.6Transfers out 19 28 3 17 0.4 0.5 0.0 0.3Crop income 731 876 2,137 1,252 13.6 15.8 28.8 20.5Livestock income 1,659 1,755 1,321 1,579 30.8 31.6 17.8 25.8Annual income 5,377 5,550 7,418 6,120 100.0 100.0 100.0 100.0Monthly income 448 463 618 510 Household size 5.90 5.88 5.77 5.85
83
Table 48: Household Income by Sub-location and Sex of Household Head (Shs)
Lelaitich Kapsabul Lugumek Total Male Female Male Female Male Female Male Female
Wage income 16,760 0 19,586 0 16,612 278 17,787 99Self employment 6,244 3,667 3,417 0 7,000 2,800 5,417 2,571Lease/rental income 0 28 154 0 26 192 67 80Transfers in 109 403 198 120 118 0 146 198Transfers out 157 39 186 0 20 0 123 17Crop income 3,108 3,268 4,533 2,717 9,685 4,840 5,814 3,711Livestock income 6,323 5,456 9,881 5,892 10,639 5,515 9,098 5,571Annual income 32,387 12,782 37,584 8,729 44,060 13,625 38,206 12,215Monthly income 2,699 1,065 3,132 727 3,672 1,135 3,184 1,018Cases 45 18 59 9 51 15 155 42Household size 6.29 4.94 6.32 3.00 6.31 3.93 6.31 4.17PERCENT Wage income 51.7 0.0 52.1 0.0 37.7 2.0 46.6 0.8Self employment 19.3 28.7 9.1 0.0 15.9 20.6 14.2 21.1Lease/rental income 0.0 0.2 0.4 0.0 0.1 1.4 0.2 0.7Transfers in 0.3 3.2 0.5 1.4 0.3 0.0 0.4 1.6Transfers out 0.5 0.3 0.5 0.0 0.0 0.0 0.3 0.1Crop income 9.6 25.6 12.1 31.1 22.0 35.5 15.2 30.4Livestock income 19.5 42.7 26.3 67.5 24.1 40.5 23.8 45.6Annual income 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Table 49: Household Income by Sub-location and Education of Household Head (Shs)
Lelaitich Kapsabul Lugumek Total None/
Nursery Prim Sec None/
Nursery Prim Sec None/
Nursery Prim Sec None/
Nursery Prim Sec
Wage income 4,506 3,689 74,846 3,095 9,987 43,733 6,299 11,500 32,200 4,852 8,356 45,879Self employment
5,172 7,296 0 884 1,935 6,933 4,420 8,400 5,400 3,838 5,592 5,124
Lease/rental income
17 0 0 0 0 506 108 0 82 48 0 272
Transfers in 341 83 0 205 286 0 200 0 0 254 136 0Transfers out 195 68 43 0 129 389 10 4 50 76 72 214Crop income 3,242 2,713 4,489 5,308 3,063 5,339 6,451 10,721 9,641 4,979 5,189 6,574Livestock income
8,417 4,361 2,988 11,985 5,869 12,577 9,357 10,289 8,138 9,648 6,666 9,323
Total annual income
21,501 18,074 82,280 21,477 21,011 68,700 26,825 40,905 55,411 23,543 25,867 66,959
Average monthly income
1,792 1,506 6,857 1,790 1,751 5,725 2,235 3,409 4,618 1,962 2,156 5,580
Cases 29 27 7 19 31 18 30 24 12 78 82 37Household size
5.10 6.59 6.57 4.68 5.77 7.33 5.10 6.46 6.08 5.00 6.24 6.78
PERCENT Wage income 21.0 20.4 91.0 14.4 47.5 63.7 23.5 28.1 58.1 20.6 32.3 68.5Self employment
24.1 40.4 0.0 4.1 9.2 10.1 16.5 20.5 9.7 16.3 21.6 7.7
Lease/rental income
0.1 0.0 0.0 0.0 0.0 0.7 0.4 0.0 0.1 0.2 0.0 0.4
Transfers in 1.6 0.5 0.0 1.0 1.4 0.0 0.7 0.0 0.0 1.1 0.5 0.0Transfers out 0.9 0.4 0.1 0.0 0.6 0.6 0.0 0.0 0.1 0.3 0.3 0.3Crop income 15.1 15.0 5.5 24.7 14.6 7.8 24.0 26.2 17.4 21.1 20.1 9.8Livestock income
39.1 24.1 3.6 55.8 27.9 18.3 34.9 25.2 14.7 41.0 25.8 13.9
Total annual income
100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
84
Table 50: Household Income by Sub-location and Age of Household Head (Shs)
Lelaitich Kapsabul Lugumek Total 20-35 36-50 >50 20-35 36-50 >50 20-35 36-50 >50 20-35 35-50 >50
Wage income
14,571 11,670 10,805 6,480 25,971 14,940 19,320 16,421 5,666 13,333 18,581 10,026
Self employment
1,989 7,598 5,472 2,220 5,014 840 5,760 6,947 5,622 3,471 6,405 4,242
Lease/rental income
0 21 0 0 296 40 49 0 120 18 124 56
Transfers in 43 50 414 35 292 195 0 0 222 24 132 281Transfers out
66 59 218 200 250 0 30 5 11 102 120 80
Crop income
2,703 3,068 3,489 3,385 4,532 4,865 9,019 9,549 7,582 5,295 5,380 5,406
Livestock income
2,860 6,253 7,706 5,341 5,714 18,462 4,242 11,386 12,005 4,291 7,414 12,306
Total annual income
22,100 28,601 27,668 17,261 41,570 39,342 38,359 44,298 31,206 26,330 37,916 32,237
Average monthly income
1,842 2,383 2,306 1,438 3,464 3,278 3,197 3,692 2,600 2,194 3,160 2,686
Cases 14 24 25 20 28 20 20 19 27 54 71 72Household size
5.36 6.92 5.24 4.20 7.18 5.75 4.65 8.05 5.00 4.67 7.32 5.29
PERCENT Wage income
65.9 40.8 39.1 37.5 62.5 38.0 50.4 37.1 18.2 50.6 49.0 31.1
Self employment
9.0 26.6 19.8 12.9 12.1 2.1 15.0 15.7 18.0 13.2 16.9 13.2
Lease/rental income
0.0 0.1 0.0 0.0 0.7 0.1 0.1 0.0 0.4 0.1 0.3 0.2
Transfers in 0.2 0.2 1.5 0.2 0.7 0.5 0.0 0.0 0.7 0.1 0.3 0.9Transfers out
0.3 0.2 0.8 1.2 0.6 0.0 0.1 0.0 0.0 0.4 0.3 0.2
Crop income
12.2 10.7 12.6 19.6 10.9 12.4 23.5 21.6 24.3 20.1 14.2 16.8
Livestock income
12.9 21.9 27.9 30.9 13.7 46.9 11.1 25.7 38.5 16.3 19.6 38.2
Total annual income
100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Table 51: Income per capita by Sub-location and Sex of Household Head (Shs)
Lelaitich Kapsabul Lugumek Total Male Female Male Female Male Female Male Female
Wage income 2,758 0 2,767 0 3,418 278 2,979 99Self employment 1,147 561 566 0 1,351 653 993 474Lease/rental income 0 5 19 0 6 192 9 71Transfers in 17 153 28 110 24 0 23 89Transfers out 24 8 32 0 4 0 20 3Crop income 533 1,226 846 1,073 1,863 3,067 1,090 1,850Livestock income 1,562 1,899 1,448 3,772 1,658 175 1,550 1,685Total annual income 5,993 3,835 5,641 4,954 8,315 4,366 6,623 4,264Average monthly income 499 320 470 413 693 364 552 355Cases 45 18 59 9 51 15 155 42Household size 6.29 4.94 6.32 3.00 6.31 3.93 6.31 4.17PERCENT Wage income 46.0 0.0 49.0 0.0 41.1 6.4 45.0 2.3Self employment 19.1 14.6 10.0 0.0 16.2 15.0 15.0 11.1Lease/rental income 0.0 0.1 0.3 0.0 0.1 4.4 0.1 1.7Transfers in 0.3 4.0 0.5 2.2 0.3 0.0 0.4 2.1Transfers out 0.4 0.2 0.6 0.0 0.0 0.0 0.3 0.1Crop income 8.9 32.0 15.0 21.7 22.4 70.3 16.5 43.4Livestock income 26.1 49.5 25.7 76.1 19.9 4.0 23.4 39.5Total annual income 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
85
Table 52: Income per capita by Sub-location and Education of Household Head (Shs)
Lelaitich Kapsabul Lugumek Total None/
nursery Prim Sec None/
nursery Prim Sec None/
nursery Prim Sec None/
nursery Prim Sec
Wage income
603 591 12,951 572 1,571 5,759 1,027 1,729 8,850 759 1,295 8,122
Self employment
1,064 1,143 0 122 499 867 771 1,799 1,031 722 1,092 756
Lease/ rental income
3 0 0 0 0 62 97 0 20 39 0 37
Transfers in 108 13 0 79 37 0 40 0 0 75 18 0Transfers out 30 10 11 0 32 49 1 1 13 11 16 30Crop income 959 467 807 1,248 585 983 2,177 1,869 2,574 1,498 922 1,466Livestock income
2,884 633 537 3,627 764 1,486 1,317 1,418 1,135 2,462 912 1,193
Total annual income
5,591 2,837 14,285 5,648 3,425 9,108 5,428 6,815 13,598 5,542 4,223 11,544
Average monthly income
466 236 1,190 471 285 759 452 568 1,133 462 352 962
Cases 29 27 7 19 31 18 30 24 12 78 82 37Household size
5.10 6.59 6.57 4.68 5.77 7.33 5.10 6.46 6.08 5.00 6.24 6.78
PERCENT Wage income
10.8 20.8 90.7 10.1 45.9 63.2 18.9 25.4 65.1 13.7 30.7 70.4
Self employment
19.0 40.3 0.0 2.2 14.6 9.5 14.2 26.4 7.6 13.0 25.8 6.5
Lease/ rental income
0.1 0.0 0.0 0.0 0.0 0.7 1.8 0.0 0.2 0.7 0.0 0.3
Transfers in 1.9 0.5 0.0 1.4 1.1 0.0 0.7 0.0 0.0 1.4 0.4 0.0Transfers out 0.5 0.4 0.1 0.0 0.9 0.5 0.0 0.0 0.1 0.2 0.4 0.3Crop income 17.1 16.5 5.6 22.1 17.1 10.8 40.1 27.4 18.9 27.0 21.8 12.7Livestock income
51.6 22.3 3.8 64.2 22.3 16.3 24.3 20.8 8.3 44.4 21.6 10.3
Total annual income
100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Table 53: Income per capita by Sub-location and Age of Household Head (Shs)
Lelaitich Kapsabul Lugumek Total 20-35 36-50 >50 20-35 36-50 >50 20-35 36-50 >50 20-35 36-50 >50
Wage income 2,957 2,303 1,098 1,500 3,377 1,935 5,310 2,454 951 3,289 2,767 1,275Self employment 344 1,180 1,143 643 650 116 1,734 996 929 969 922 777Lease/rental income 0 3 0 0 37 4 12 0 108 5 16 42Transfers in 8 9 127 9 35 75 0 0 44 5 17 82Transfers out 12 9 33 50 31 0 8 1 1 25 16 12Crop income 595 493 1,036 993 634 1,097 2,651 1,139 2,459 1,504 722 1,586Livestock income 547 851 3,056 841 640 4,231 702 1,498 1,654 713 941 2,857Total annual income 4,440 4,830 6,426 3,935 5,342 7,458 10,401 6,088 6,143 6,461 5,369 6,607Average monthly income 370 403 536 328 445 621 867 507 512 538 447 551Cases 14 24 25 20 28 20 20 19 27 54 71 72Household size 5.36 6.92 5.24 4.20 7.18 5.75 4.65 8.05 5.00 4.67 7.32 5.29PERCENT Wage income 66.6 47.7 17.1 38.1 63.2 25.9 51.1 40.3 15.5 50.9 51.5 19.3Self employment 7.7 24.4 17.8 16.3 12.2 1.6 16.7 16.4 15.1 15.0 17.2 11.8Lease/rental income 0.0 0.1 0.0 0.0 0.7 0.0 0.1 0.0 1.8 0.1 0.3 0.6Transfers in 0.2 0.2 2.0 0.2 0.7 1.0 0.0 0.0 0.7 0.1 0.3 1.2Transfers out 0.3 0.2 0.5 1.3 0.6 0.0 0.1 0.0 0.0 0.4 0.3 0.2Crop income 13.4 10.2 16.1 25.2 11.9 14.7 25.5 18.7 40.0 23.3 13.4 24.0Livestock income 12.3 17.6 47.6 21.4 12.0 56.7 6.7 24.6 26.9 11.0 17.5 43.2Total annual income 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
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Table 54: Households by Land Owned and Accessed (acres)
Land owned (within district)
Land owned (outside district)
Land owned (total)
Land accessed (parent)
Land accessed (other)
Land accessed (total)
Lelaitich 3.86 0.00 3.86 1.30 0.02 1.31Kapsabul 3.79 0.66 4.45 2.00 0.06 2.06Lugumek 5.24 1.13 6.37 1.60 0.05 1.64Total 4.30 0.61 4.91 1.64 0.04 1.68 Table 55: Households by Land Owned and Accessed by Sex of Household Head (acres)
Land owned (within district)
Land owned (outside district)
Land owned (total)
Accessed (parent)
Accessed (other)
Accessed (total)
Lelaitich Male 3.55 0.00 3.55 1.56 0.02 1.58 Female 4.64 0.00 4.64 0.64 0.00 0.64
Kapsabul Male 3.78 0.46 4.24 2.08 0.07 2.15 Female 3.83 2.00 5.83 1.44 0.00 1.44
Lugumek Male 4.84 0.98 5.82 1.86 0.06 1.92 Female 6.60 1.63 8.23 0.70 0.00 0.70
Total Male 4.06 0.50 4.56 1.86 0.05 1.91 Female 5.17 1.01 6.18 0.83 0.00 0.83
Table 56: Households by Land Owned and Accessed by Education of Household Head (acres)
Land owned (within district)
Land owned (outside district)
Land owned (total)
Accessed (parent)
Accessed (other)
Accessed (total)
Lelaitich None/ nursery
5.55 0.00 5.55 0.88 0.00 0.88
Primary 1.34 0.00 1.34 1.80 0.04 1.84 Secondary 6.57 0.00 6.57 1.07 0.00 1.07
Kapsabul None/ nursery
6.00 0.11 6.11 1.37 0.00 1.37
Primary 0.77 0.16 0.94 2.55 0.06 2.61 Secondary 6.64 2.11 8.75 1.72 0.11 1.83
Lugumek None/ nursery
9.73 1.85 11.58 0.63 0.00 0.63
Primary 1.63 0.54 2.17 2.17 0.13 2.29 Secondary 1.25 0.50 1.75 2.88 0.00 2.88
Total None/ nursery
7.27 0.74 8.01 0.90 0.00 0.90
Primary 1.21 0.22 1.43 2.19 0.07 2.26 Secondary 4.88 1.19 6.07 1.97 0.05 2.03
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Table 57: Households by Land Owned and Accessed by Age of Household Head (acres)
Land owned (within
district)
Landowned (outside
district)
Landowned (total)
Accessed (parent)
Accessed (other)
Accessed (total)
Lelaitich 20-35 0.44 0.00 0.44 2.14 0.00 2.14 36-50 2.75 0.00 2.75 1.55 0.04 1.59 >50 6.84 0.00 6.84 0.58 0.00 0.58
Kapsabul 20-35 0.68 0.90 1.58 2.30 0.20 2.50 36-50 1.73 0.00 1.73 2.79 0.00 2.79 >50 9.78 1.35 11.13 0.60 0.00 0.60
Lugumek 20-35 0.00 0.30 0.30 2.95 0.15 3.10 36-50 2.37 0.47 2.84 2.05 0.00 2.05 >50 11.15 2.20 13.35 0.28 0.00 0.28
Total 20-35 0.36 0.44 0.81 2.50 0.13 2.63 35-50 2.25 0.13 2.37 2.17 0.01 2.18 >50 9.27 1.20 10.47 0.47 0.00 0.47
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Table 58: Household Consumption per Month (Shs)
Lelaitich Kapsabul Lugumek Total Total Male Female
PURCHASES Cereals 846 1,085 681 873 936 640Beans 63 148 72 96 107 55Meat/ eggs 214 164 163 180 188 151Fats 47 68 73 63 70 36Fruits/ vegetables 173 203 169 182 192 145Roots 27 70 31 43 49 20Milk 110 145 44 100 109 68Sugar 204 273 230 236 243 213Salt 16 23 18 19 19 17Beverages 76 97 83 86 89 72Other foods 70 32 23 41 48 18Fuel 127 136 77 113 116 103Household operations 108 153 139 134 149 76Alcohol 164 116 38 105 121 48Tobacco 16 19 4 13 14 11Transport 80 71 77 76 88 33Personal care 12 11 7 10 11 8Health 45 58 290 131 127 148Clothing 113 135 137 128 148 55Footwear 30 59 46 45 52 20Education 139 387 188 241 278 103Other non-regular 3 13 7 8 10 0
OWN CONSUMPTION Maize 300 353 370 342 366 252Millet 5 1 15 7 7 7Sorghum 7 0 5 4 4 5Beans 30 17 20 22 21 25Sweet potatoes 33 14 3 16 17 13Cattle 71 55 68 65 63 71Goat 21 13 11 15 15 14Sheep 10 2 0 4 5 0Chicken 8 9 9 9 10 3Milk (cattle) 189 374 291 287 293 264Milk (goat) 9 4 0 4 4 5Eggs 20 14 16 17 19 8
Food purchases 1,845 2,308 1,587 1,918 2,049 1,435Non-food purchases 836 1,157 1,010 1,005 1,114 603Own consumption 704 857 808 791 825 668Total food 2,549 3,164 2,395 2,710 2,874 2,103Total non-food 836 1,157 1,010 1,005 1,114 603TOTAL 3,384 4,321 3,405 3,715 3,988 2,706
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Table 59: Household Consumption Patterns (%)
Lelaitich Kapsabul Lugumek Total Total Male Female
PURCHASES Cereals 25.0 25.1 20.0 23.5 23.5 23.7Beans 1.9 3.4 2.1 2.6 2.7 2.0Meat/ eggs 6.3 3.8 4.8 4.8 4.7 5.6Fats 1.4 1.6 2.1 1.7 1.8 1.3Fruits/ vegetables 5.1 4.7 5.0 4.9 4.8 5.4Roots 0.8 1.6 0.9 1.2 1.2 0.8Milk 3.2 3.4 1.3 2.7 2.7 2.5Sugar 6.0 6.3 6.7 6.4 6.1 7.9Salt 0.5 0.5 0.5 0.5 0.5 0.6Beverages 2.3 2.2 2.4 2.3 2.2 2.6Other foods 2.1 0.7 0.7 1.1 1.2 0.7Fuel 3.7 3.2 2.3 3.1 2.9 3.8Household operations 3.2 3.5 4.1 3.6 3.7 2.8Alcohol 4.8 2.7 1.1 2.8 3.0 1.8Tobacco 0.5 0.4 0.1 0.4 0.3 0.4Transport 2.4 1.6 2.3 2.0 2.2 1.2Personal care 0.3 0.2 0.2 0.3 0.3 0.3Health 1.3 1.3 8.5 3.5 3.2 5.5Clothing 3.3 3.1 4.0 3.5 3.7 2.0Footwear 0.9 1.4 1.3 1.2 1.3 0.7Education 4.1 9.0 5.5 6.5 7.0 3.8Other non-regular 0.1 0.3 0.2 0.2 0.2 0.0
OWN CONSUMPTION Maize 8.9 8.2 10.9 9.2 9.2 9.3Millet 0.1 0.0 0.4 0.2 0.2 0.3Sorghum 0.2 0.0 0.1 0.1 0.1 0.2Beans 0.9 0.4 0.6 0.6 0.5 0.9Sweet potatoes 1.0 0.3 0.1 0.4 0.4 0.5Cattle 2.1 1.3 2.0 1.7 1.6 2.6Goat 0.6 0.3 0.3 0.4 0.4 0.5Sheep 0.3 0.1 0.0 0.1 0.1 0.0Chicken 0.2 0.2 0.3 0.2 0.3 0.1Milk (cattle) 5.6 8.6 8.5 7.7 7.3 9.8Milk (goat) 0.3 0.1 0.0 0.1 0.1 0.2Eggs 0.6 0.3 0.5 0.4 0.5 0.3
Food purchases 54.5 53.4 46.6 51.6 51.4 53.0Non-food purchases 24.7 26.8 29.7 27.1 27.9 22.3Own consumption 20.8 19.8 23.7 21.3 20.7 24.7Total food 75.3 73.2 70.3 72.9 72.1 77.7Total non-food 24.7 26.8 29.7 27.1 27.9 22.3TOTAL 100.0 100.0 100.0 100.0 100.0 100.0
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Table 60: Household Consumption per Capita (Shs)
Lelaitich Kapsabul Lugumek Total Total Male Female
PURCHASES Cereals 164 208 140 171 164 197Beans 15 26 17 19 19 18Meat/ eggs 45 37 38 40 36 52Fats 10 13 15 13 13 13Fruits/ vegetables 32 40 34 36 33 47Roots 5 13 6 8 9 5Milk 23 32 9 22 21 25Sugar 47 58 48 51 43 81Salt 4 5 4 4 3 7Beverages 17 20 17 18 16 25Other foods 14 7 5 9 10 4Fuel 30 30 16 25 21 42Household operations 23 30 29 28 28 28Alcohol 27 27 7 20 24 8Tobacco 3 5 1 3 4 2Transport 14 12 14 13 15 6Personal care 2 2 1 2 2 2Health 8 20 56 28 20 59Clothing 21 24 29 25 27 16Footwear 6 13 9 10 11 6Education 21 58 28 36 40 21Other non-regular 1 2 1 1 2 0
OWN CONSUMPTION Maize 72 69 79 73 66 102Millet 1 0 4 2 1 4Sorghum 1 0 3 1 1 3Beans 6 3 7 5 4 10Sweet potatoes 6 3 0 3 3 3Cattle 21 6 11 12 9 25Goat 5 2 3 3 3 3Sheep 1 0 0 0 1 0Chicken 1 2 2 2 2 1Milk (cattle) 37 70 75 61 47 114Milk (goat) 2 1 0 1 1 1Eggs 4 2 3 3 3 2
Food purchases 376 459 333 390 368 474Non-food purchases 156 222 194 191 192 190Own consumption 157 159 187 167 140 267Total food 533 617 520 558 508 741Total non-food 156 222 194 191 192 190TOTAL 689 839 714 749 700 931
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Table 61: Household Consumption per Capita (%)
Lelaitich Kapsabul Lugumek Total Total Male Female
PURCHASES Cereals 23.9 24.8 19.6 22.9 23.5 21.1Beans 2.1 3.1 2.3 2.6 2.8 2.0Meat/ eggs 6.5 4.4 5.3 5.3 5.2 5.6Fats 1.5 1.5 2.2 1.7 1.8 1.4Fruits/ vegetables 4.7 4.8 4.7 4.7 4.7 5.0Roots 0.7 1.6 0.9 1.1 1.3 0.6Milk 3.4 3.8 1.3 2.9 2.9 2.7Sugar 6.9 6.9 6.8 6.8 6.2 8.7Salt 0.5 0.6 0.5 0.6 0.5 0.7Beverages 2.5 2.3 2.3 2.4 2.3 2.7Other foods 2.0 0.8 0.7 1.2 1.4 0.4Fuel 4.3 3.5 2.3 3.4 2.9 4.5Household operations 3.4 3.6 4.1 3.7 4.0 3.0Alcohol 3.9 3.2 1.0 2.7 3.4 0.9Tobacco 0.5 0.6 0.1 0.4 0.5 0.2Transport 2.0 1.4 2.0 1.8 2.2 0.6Personal care 0.3 0.2 0.2 0.2 0.3 0.2Health 1.2 2.4 7.9 3.8 2.9 6.4Clothing 3.0 2.8 4.1 3.3 3.8 1.7Footwear 0.9 1.5 1.3 1.3 1.5 0.7Education 3.0 6.9 4.0 4.8 5.7 2.3Other non-regular 0.1 0.2 0.2 0.2 0.2 0.0
OWN CONSUMPTION Maize 10.4 8.2 11.1 9.8 9.4 10.9Millet 0.1 0.0 0.5 0.2 0.2 0.4Sorghum 0.2 0.0 0.4 0.2 0.1 0.4Beans 0.8 0.3 0.9 0.7 0.6 1.0Sweet potatoes 0.9 0.3 0.1 0.4 0.4 0.3Cattle 3.1 0.7 1.6 1.7 1.3 2.7Goat 0.7 0.2 0.4 0.4 0.5 0.3Sheep 0.2 0.0 0.0 0.1 0.1 0.0Chicken 0.2 0.3 0.2 0.2 0.3 0.1Milk (cattle) 5.4 8.4 10.5 8.2 6.7 12.3Milk (goat) 0.3 0.1 0.0 0.1 0.1 0.1Eggs 0.5 0.3 0.4 0.4 0.5 0.2
Food purchases 54.6 54.7 46.7 52.1 52.5 50.9Non-food purchases 22.6 26.4 27.2 25.5 27.4 20.4Own consumption 22.8 18.9 26.1 22.3 20.1 28.6Total food 77.4 73.6 72.8 74.5 72.6 79.6Total non-food 22.6 26.4 27.2 25.5 27.4 20.4TOTAL 100.0 100.0 100.0 100.0 100.0 100.0
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Table 62: Estimated Calorie and Protein Availability per Adult Equivalent
Lelaitich Kapsabul Lugumek Total Total Male Female
CALORIES Cereals 1,727 1,990 1,601 1,776 1,678 2,135Beans 51 69 57 59 58 63Meat 51 32 40 41 36 60Milk/ eggs 253 289 232 259 241 322Vegetables 37 46 38 40 38 51Roots 36 52 22 37 40 26Sugar 163 190 160 171 150 252TOTAL 2,318 2,668 2,151 2,383 2,240 2,909
PROTEINS Cereals 64 75 60 67 63 80Beans 3 5 4 4 4 4Meat 9 6 7 7 6 11Milk/ eggs 16 16 13 15 15 17Vegetables 2 3 2 2 2 3Roots 1 1 1 1 1 1TOTAL 96 105 87 96 91 116
CALORIES (%) Cereals 74.5 74.6 74.5 74.5 74.9 73.4Beans 2.2 2.6 2.6 2.5 2.6 2.2Meat 2.2 1.2 1.9 1.7 1.6 2.1Milk/ eggs 10.9 10.8 10.8 10.9 10.8 11.1Vegetables 1.6 1.7 1.8 1.7 1.7 1.8Roots 1.6 1.9 1.0 1.5 1.8 0.9Sugar 7.0 7.1 7.5 7.2 6.7 8.7TOTAL 100.0 100.0 100.0 100.0 100.0 100.0
PROTEINS (%) Cereals 66.9 70.9 69.1 69.1 69.1 69.0Beans 3.6 4.4 4.5 4.2 4.3 3.7Meat 9.6 5.6 8.3 7.7 7.0 9.6Milk/ eggs 16.8 15.3 14.8 15.6 16.0 14.5Vegetables 2.3 2.6 2.7 2.5 2.5 2.6Roots 0.9 1.2 0.6 0.9 1.0 0.5TOTAL 100.0 100.0 100.0 100.0 100.0 100.0
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ACTIONAID-KENYA
BOMET DEVELOPMENT INITIATIVE
LELAITICH BASELINE SURVEY
SURVEY INSTRUMENTS AND ENUMERATORS’ REFERENCE MANUAL
3 December 1997
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ENUMERATORS’ REFERENCE MANUAL
INTRODUCTION Background Information 1. ACTIONAID-Kenya Bomet Development Initiative (DI) was initiated in July 1996 as a follow-up and in response to the national study that identified the district as one of the poorest in Kenya. The selection of Bomet as a new development initiative is in line with AAK’s strategy to focus on the poorest communities in some of the most vulnerable areas in the country. The district was subsequently recommended for AAK’s intervention focusing on poverty alleviation. The initiative became operational in September 1996. 2. Efforts to improve the wellbeing of the poor can only be effective if seen in the context of the community, particularly at the household level. However, given the absence of benchmark information on which interventions could be based, it was difficult to identify the real problems facing the community. The participatory rural appraisal (PRA) undertaken in October 1996 established that, of the 1,518 households in the operational area, i.e. Lelaitich location, 64.6% were classified as poor. Although the PRA generated a lot of useful data, there is still need for deeper analysis on the root causes of poverty and the coping mechanisms adopted by households and the community using a detailed household income and expenditure survey. The survey findings are expected to lead to better understanding of poverty and its concomitant effects on household food security, education, health, and environmental sanitation. Objectives of the Survey 3. The main objectives of the study are: (a) To provide baseline information required for targeting interventions on critical development
issues in the operational area; (b) To empower the DI staff with information that is required for participatory planning of
development initiatives supported by AAK; (c) To collect from households/ community/ institutions and analyze existing data which would
form a benchmark for subsequent monitoring and evaluation of the impact of the DI on the population, especially on vulnerable groups;
(d) To inquire into the methods adopted by the population so as to cope with the constraints arising
from poverty and social exclusion; and (e) To draw conclusions and make recommendations on possible areas of intervention and strategic
objectives AAK should pursue to make an impact in the area. 4. This manual is designed to guide enumerators and supervisors during the data collection phase of the survey. The manual defines main concepts used in the survey and presents procedures to be followed in completing each section of the questionnaire. Geographical codes are presented in the appendix. 5. The following questionnaires will be administered in this survey: (a) Household Composition (Form B/S/L/1) (b) Child Immunization and Breastfeeding (Form B/S/L/2)
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(c) Housing, Amenities and Assets (Form B/S/L/3) (d) Household Regular Purchases for one Month (Forms B/S/L/4A and B/S/L/4B) (e) Household Non-regular Purchases for one Year (Form B/S/L/5) (f) Crop Production and Disposal (Forms B/S/L/6A and B/S/L/6B) (g) Livestock Production and Disposal (Form B/S/L/7) (h) Household Non-Agricultural Income (Form B/S/L/8)
SURVEY DESCRIPTION AND ORGANIZATION Survey Coverage and Methodology 6. The survey is to be carried out in the three sub-locations of Lelaitich location, namely, Lelaitich (with 508 households), Kapsabul (528 households) and Lugumek (482 households). Based on a 15% sampling fraction, the survey will cover about 228 households out of 1,518 households. 7. It is possible to fail to locate a selected household during the enumeration. The rules to guide in replacing a selected household are: (a) If a household moved within the same sub-location and can be located, tag/follow and interview
it. (b) If the household moved out of the sub-location or cannot be located after moving from the
sampled dwelling unit, then REPLACE with the household currently occupying the selected dwelling unit, and indicate the replacement in the identification particulars section of Form B/S/L/1.
Sample Design 8. The administrative decisions that dictated the Lelaitich sample design include:
a) That the survey should include all villages in the location; b) That the spatial unit of analysis would be the sub-location.
9. The total number of households included in the lists from the PRA was 1,518. Upon receipt of the lists, the first step was to organize the villages by sub-location and then assigning numbers to households beginning with 1 so that one sub-location became a stratum. The use of the term “strata” therefore refers to classification of households by sub-location. The second step was to select the total sample proportionate to the size of each stratum. The required sample was generated by use of systematic selection with a random start. 10. In each sample, each element had an equal chance of selection. Therefore each element has the weight of 1 in the sample total, and F=1/f in the population total, where f is the selection fraction. Since the sampling fraction in each stratum was equal to the sampling fraction for the universe, the procedure ensured a self-weighting sample8. 8. Rounding of the strata sample to the nearest integer introduces slight departures in the values of actual sampling fractions. However, this trivial departure is usually ignored (Kish, 1965).
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11. The basic weights, before adjustment for non-response, are the reciprocals of the probabilities of selection, i.e. w = m/n Where: w is the weight in the stratum;
m is the total number of households in the stratum; and n is the sample size in the stratum.
12. In producing survey estimates, the basic weights will be adjusted for non-response to arrive at final adjusted weight, which is the product of the basic weight and a non-response adjustment factor. The procedure of calculating the non-response (nr) factor for each stratum was as follows: nr = n/i Where: nr = the non-response adjustment factor;
n = the total number of originally selected households; i = the number of households which responded
The adjusted weights are wa = w * nr = (m/n)*(n/i) = m/i, i.e. the total number of households divided by the number of households which responded.
ESTIMATION PROCEDURES Blanks and Non-Response 13. There are various sources of errors/ bias in a sample survey or census. Errors could be introduced by misreporting, lack of data, enumerator or respondent bias, non-response, and in data entry. This section deals with non-response and its effects on sample weights. In a household survey, non-response could be introduced through refusals and failure to locate a household. Although it is difficult to rule out inclusion in the frame (N) of some households which did not exist or to exclude some which existed before the frame was constructed, i.e. out-of-scope, it was decided to treat the sample frame (N) as a true report of the number of households in December 1997. Therefore refusals and failure to locate will be summed as non-response. 14. Filled survey and census questionnaires may contain blanks or missing values attributable to lack of data or a question that was not asked. Blanks and non-response splits the original population (N) into two subclasses: M non-blank members and B blanks and non-response, i.e. N=M+B. The presence of blanks and non-response introduces variation in the size of the sample. This variation is a function of the proportion M=M/N. However, the selection interval (k) and selection fraction (f) do not change since the blanks and non-response were identified after the original sample had been selected.
PRE-TEST 15. A two-day training of enumerators was conducted during 25-26 November 1997. The training was conducted using the draft questionnaires and the enumerators’ reference manual. At the end of the training, the 12 enumerators formed four groups of three persons each to pre-test on each other. One person in the group acted as the respondent, the second as the enumerator, and the third took notes on the enumeration process. Each enumerator also conducted pre-tests on a household in the community, and a final debriefing meeting held to review the training phase of the survey. The pre-tests found inadequacies in the survey instruments especially on land tenure, which led to amendment of the draft questionnaire. The average interview time was one and a half hours. There were no reports of respondent fatigue. It was therefore decided to retain the length of the questionnaire.
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PRINCIPLES OF INTERVIEWING
16. This section of the manual gives a summary of some important points to be kept in mind when conducting personal interviews during the survey. Interviewing is a Specialized Art 17. Interviewing involves two people -- interviewer and the respondent. Interviewing facilitates obtaining of information from someone by asking an organized set of questions designed for a purpose. Interviewing differs from ordinary conversation in several respects: (a) The interviewer and the respondent are strangers to each other. One of the main tasks is to gain
the confidence of the respondent so that he/she is at ease and willing to answer the questions you ask.
(b) Unlike normal conversation, one person is asking all the questions and the other person
answering them all. You must refrain from giving your opinion until you have completed the interview. You must not react in any way to what the respondent tells you. Never show disapproval but probe in a manner that should not offend the respondent. At all times throughout the interview you must remain neutral. However, you should show interest in the answers by nodding your head or saying something like “I see” or “Yes”.
(c) There is a strict sequence of questions that must be asked. You must always be in control of the
situation. This means you must maintain the interest of the respondent throughout the interview. The enumerator should prepare (head-tune) the respondent when starting to ask questions on a particular Form (record type), i.e. state the type of information being solicited, so to ease communication with the respondent. The record type (RT) is used in data entry to identify the Form.
Gaining Access to the Respondent 18. Although you and the respondent are strangers to each other, you must approach the respondent and in a very short time, gain his/her confidence and cooperation so that he/she will answer all the questions. First impressions of your appearance and the things you say and do are of vital importance in gaining the respondent’s cooperation. Therefore, you must be sure that your appearance and behaviour are acceptable to the respondent and also to other people in the area in which you will be interviewing. On meeting the respondent (preferably the head of the household) the first thing you should do is introduce yourself stating your name, the agency you are working for, and what you want of the respondent. A good introduction may be something like:
Good morning. I am Kipng’eno Rotich and I am here on behalf of ACTIONAID-Kenya. My visit this morning is part of the Lelaitich Baseline Survey. Your household is one of the many chosen in Lelaitich location for this study. The information I get from you will be confidential. The information will be pooled together and be used to obtain knowledge on livelihoods systems. This information will then be used in formulating policy for planning purposes and economic development. The baseline study is intended to define the starting point for the AAK programme and will be used to (a) identify community development priorities, and (b) assess achievements of the programme when subsequent surveys are conducted to see if there are changes as compared to the “baseline”.
Confidentiality 19. All information collected from the households is strictly confidential. No individual report is to be released to anyone. Because some of the questions to be asked are personal, the interview should not be conducted in the presence of visitors unless the respondent, having first learnt the nature of the
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survey, has no objection. Also, you should never mention other interviews or show completed questionnaires to other enumerators or supervisors in front of a respondent or any other persons. Neutrality 20. Apart from confidentiality, most people are polite, especially to strangers, and they tend to give answers that they think will please the interviewer. It is therefore extremely important that you remain absolutely neutral towards the subject matter of the interview. Do not show surprise, approval, or disapproval of the respondent’s answer by your tone of voice or facial expression. Probing 21. It is possible that the respondent’s answer to a question is not satisfactory. From what is required, his/her answer may be incomplete or irrelevant, or sometimes he/she may be unable to answer the question as put to him/her. If this happens, then asking some additional questions is required to obtain a complete answer to the original question. Asking additional questions to obtain a complete answer is called ‘probing’. The probes must be worded so that they are “neutral” and do not lead the respondent in a particular direction. Remember that the quality of data to be collected depends very much on the enumerator’s ability to probe correctly. In probing you should ensure that the meaning of the question is not changed. To minimize the probing process, make sure that you maintain your presence of mind. Recording Answers 22. Each answer must be recorded in the correct cell in the questionnaire. Before leaving the respondent you should check to see that all required questions have been answered. If the question requires a numerical answer, be sure to enter the appropriate number or zero if the answer is “None”. If a column is left blank for questions requiring numerical answers or numerical codes, it is impossible to tell whether or not the question was asked or answered. Blanks and “0” have very different meanings when the survey is analyzed. Always visit the respondent with the correct Forms. Never rely on taking answers in a notebook for transfer later. This is a bad habit and only complicates your work. Record what the respondent says, not your own interpretation/ summary. Nonetheless, if a respondent gives an answer that contradicts an earlier response, confirm the true position by probing. Making Appointments 23. You should always try to arrange beforehand for a suitable time for interviewing the respondent. You should never try to force the respondent to attend at a time that would obviously be inconvenient to him/her. Once a time has been set for an interview it is important that you keep the appointment. Being late for appointments inconvenience respondents and results in unpleasant situations. Handling Reluctant Respondents 24. Actual refusals are rare and for most enumerators there will be no refusals. If refusals come often, then there is something wrong with the way you are introducing yourself or explaining the use of the survey. If the enumerator continues to have problems, he/she should contact his/her supervisor at once. The person who says he does not have time for the interview is usually trying to put you off. Ordinarily a statement such as “this won’t take very long” or “I can ask you some questions while you are working” will start the ball rolling and soon he/she will give you his entire attention. Always be honest. Never tell a respondent that the interview will take only ten minutes if you believe forty minutes will be needed. If he really does not have the time, make an appointment for a return visit. A good enumerator is proud of his ability to meet people with ease and friendliness and to secure their cooperation.
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Call-Back Procedures 25. It is important that you attempt to interview the head of the household, but occasionally you may need to make a second visit if the head of the household (or other members) is not present. Most of the questions that are contained in the questionnaire can only be answered by the head of the household or another person next in line taking the responsibility of the head of the household. Do not try to complete the questionnaire by interviewing children or other persons who are not familiar with the household. Enumerator Review of Questionnaires 26. As soon as possible after leaving the respondent, the enumerator must check over the questionnaire carefully to see that all the answers are complete. In some cases it may be necessary to revisit the respondent for more complete information and this is the time to do it. Under the pressure to complete an interview, some enumerators become lazy in checking over each questionnaire while the interview is fresh in their minds. This part of the job should never be overlooked. Experience has shown that most of the problems involving completed questionnaires could have been eliminated by the enumerator if he/she had made a check of the questionnaire before handing it over to the supervisor. The enumerator should therefore plan his workload to include some time for checking the questionnaire. Language and Translation 27. Interview the respondent in the language in which he/she feels most comfortable. If he/she prefers English, do the interview in English. If the respondent is most comfortable in Kiswahili, then speak Kiswahili. If he/she speaks only another language you understand, then you can do the interview in that language. If the respondent speaks only a language you do not understand, then you must raise this problem with your supervisor. In translating and probing, be sure you do not give the answer you expect. When translating certain words, it is essential that the question is framed in such a way that it would mean the same as in the English phrasing of the questionnaire. There may be particular difficulty with the word ‘work’. In many languages, when a person is asked “Do you work?” it means “Are you employed by someone else for pay?” Try to avoid this type of misunderstanding when you are asking questions in other languages. Ending the Interview 28. After completing the interview, thank the respondent for his/her time and cooperation and leave the way open for a future interview. Even if the respondent is very friendly, you should always avoid overstaying your welcome.
CONCEPTS AND DEFINITIONS 29. For the survey to serve its intended purpose and avoid data misinterpretation, it is important that information collected refer to the same items or universe. To this end, this section attempts to explain concepts and unfamiliar terms used in the questionnaire so that they are understood uniformly and used consistently during the training, data collection, and analysis. Below are common concepts and definitions used in the survey. Household 30. A household is defined as a person or a group of persons residing in the same home or compound, and are answerable to the same head and share a common source of food. There are three important ways of identifying whether you are dealing with the same household:
(a) Whether the people reside in the same compound; (b) Whether they are answerable to the same head; and
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(c) Whether they pool and share their resources.
If the answer to each of the above criteria is “Yes”, then you are sure that you are dealing with one household. If any of them is “No”, then you may be dealing with more than one household. 31. The survey is mainly interested in the de jure (usual resident) household members, i.e. persons who normally live in the household. Under this definition, polygamous wives living within a single compound are included in the same household regardless of the cooking arrangements. Domestic servants who have meals with the household should be included as household members. If the servants cook and eat separately, they should be listed as separate households. Head of Household 32. The head of a household is a person who is regarded by the other members of the household as its head, and may be a man or a woman. Respondent 33. Any member of the household who provides information to the interviewer. In this survey, the respondent must be an adult member of the household competent to answer questions on the household. Holding 34. A holding is the land associated with a household, being used wholly or partially for agricultural purposes and being managed as a single economic unit under the overall control of a holder. A holder is the person with overall control over the management of the holding. Dwelling Unit 35. A place of residence for a family, an individual or a group of persons eating together and sharing the same budget for common provisions. Household Income 36. The sum of money income and income in kind and consists of receipts which, as a rule, are of a recurring nature and accrue to the household or to individual members of the household regularly at annual or more frequent intervals. Main Economic Activity 37. Economic activity/industry is defined in terms of type of goods produced or services supplied by the unit/establishment in which the person works. Therefore, if a person reports working in a factory producing suitcases and handbags, the detailed activity would be “Tanning and dressing of leather, manufacture of luggage, handbags, saddler and harness” falling under the major group labelled “Manufacturing”. Occupation 38. An occupation is the smallest segment of work which is specifically identified in the occupational classification system. It refers to the type of work one was doing during the reference period regardless of the economic activity in which one may be employed or the type of training received. For example, a stenographer may work in a school, voluntary organization, Government office, etc. Occupationally, she remains a stenographer as long as she performs the same kind of work. However, if her main duties change to those of general office clerk, then she can no longer be classified as stenographer. A mere
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change of employers doesn’t change the occupation as long as the principal tasks remain the same. It is also important to distinguish between occupation (duties performed) and education/ training received. Enterprise 39. For the purpose of this survey, an enterprise is an entity which exclusively or principally carries out a single type of economic activity at a single physical location. In the case of commercial banks, an enterprise would be a branch at a specific location. Likewise in the hotel industry, a chain of hotels with different locations and names, but under the same management would be considered as separate enterprises. There are, however, some complications in this definition because some units are hard to locate physically due to the nature of their activities. Thus construction workers such as masons may carry out daily activities at different worksites which are far away from each other, while self-employed taxi drivers and peddlers/ hawkers/ tinkerers (travelling menders of metal household utensils) have unlimited worksites. Urban area 40. These consist of all towns which, according to the Kenya 1989 Population and Housing Census, had 2,000 residents or more.
INSTRUCTIONS FOR COMPLETING THE QUESTIONNAIRE FILLING THE IDENTIFICATION PARTICULARS 41. All the schedules have a common identification section at the top. You will be provided with a list of households. A complete list of district codes is given in the Appendix of this manual. For this section: i) Enter your name and your Supervisor’s name in the upper left hand corner of each Form. ii) Write the name of the sub-location and village in which the household is located, and enter the
sub-location and village codes in columns 2 to 4. iii) You will be supplied with a list of selected households to interview for the survey. Enter the
household number in columns 5-7. If household is 3, enter 003. If you write 3 in column 6, this will be taken as household 030. Avoid this problem by filling all the columns for household number.
iv) Enter the date of interview. v) Indicate in the space provided whether the household interviewed was a replacement from the
list provided to you. 42. The sub-location codes are:
1= Lelaitich 2= Kapsabul 3= Lugumek
43. The village codes are: Lelaitich sub-location 01. Lelaitich (42 households) 02. Cheptare (57)
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03. Mabutek (57) 04. Terta (30) 05. Chepkebit (36) 06. Kapsasian South (21) 07. Kapsasian North (29) 08. Kapkwen - Nyak (20) 09. Nyakichiwa (26) 10. Sumelei (36) 11. Koita (21) 12. Kapkwen-Lelaitich (51) 13. Kipsirat (49) 14. Simotwet (33) Kapsabul sub-location 01. Simotwet (52) 02. Cheboiwo (29) 03. Kapinderem (39) 04. Chepkirabach (33) 05. Cheptebes (40) 06. Chemengwa (33) 07. Cheronye (33) 08. Boreiwek (37) 09. Chematich (42) 10. Uswet (37) 11. Kaptororgo (33) 12. Kapkoros (41) 13. Kapsabul (43) 14. Kiptenden (36) Lugumek sub-location 01. Lugumek Central (38) 02. Chebitoik (49) 03. Kosia South (57) 04. Kosia North (55) 05. Chebunge (48) 06. Lugumek North (38) 07. Koita (35) 08. Lugumek West (38) 09. Kapchemoino (32) 10. Chepkoin (61) 11. Kipsirichet (31) Final Interview Status 44. Indicate final interview status in column 10. Final interview status can fall under the following categories:
Code Interview Status
1 Completed 2 Partial 3 Vacant - housing unit not occupied. No people live there
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4 Unable to contact on vacation, or unable to get an appointment (but household
is cooperative, i.e. not refusing) 5 Refusal -- household refused to be interviewed. Household shows resistance
after repeated attempts 6 Unable to interview due to age, illness or impairment 7 Unable to interview due to language 8 Out-of-scope - dignitaries, foreigners intending to leave Kenya before survey
ends, etc. 9 Other (specify)
HOUSEHOLD COMPOSITION: FORM B/S/L/1 45. This form labelled B/S/L/1 is to be used to record information on the usual household members. For a household having 12 or fewer members, only one copy of the Form is necessary. If there are more than 12 members, then you will fill two Forms, starting the first row of the second Form with serial number 13. Serial Number 46. The first person should be the head of the household and will be Serial Number 01, the second 02, and so on. If you continue to another Form, the first person on the second Form will be serial number 13, and all identification particulars should be the same as those given in the first Form as they refer to the same household. Name of household member 47. The list of respondents given to you gives the name of the household head selected for the survey. You must locate this person and enter his/her particulars on the first line of the Form, provided he/she is still a usual member of the household. The name of each person is entered under column headed “Name”. Enter sufficient details to allow identification of the person in case of call-backs or re-interview. Relationship to head 48. For each listed member write his/her relationship to the household head by blood or marriage. Enter the relevant relationship code. In cases where several persons who are not related by blood or marriage constitute a household as common in urban areas, code one of them as “Head” and the rest “Unrelated”. Sex 49. Write in the space provided “M” for male and “F” for female and enter codes 1 and 2, respectively. The enumerator must ask the sex of small children when in doubt.
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Age 50. “How old is...?” Enter the age of the person in completed years in the two boxes provided9. A child under one year of age should be coded as “00”. Anyone aged 100 or over should be coded as “99”. Do not round the age to end in “0”, “5” or other preferred digit. The recorded age of children below one year will be misleading if the reference date is taken to be the date of the interview since all households will not be interviewed on the same day. To correct the problem, any child whose first birthday will be on or before 15 December 1997 will be entered as 00 since this is the date the survey is expected to end. 51. It is sometimes possible to estimate a person’s age by relating his/her birth to a notable event if they can indicate how old he/she was when the event occurred or how many years elapsed before his/her birth. The calendar of events for the Kipsigis country (Kericho and Bomet districts) includes: 1906: Kosigo age group (circumcision) 1910: Nyongi age group (circumcision) 1914: First World War referred to by the Kipsigis as “Lugetab Jeruman” 1918: Maina age group (“Ma’syema”) circumcision 1921: Second Maina age group 1924: Third Maina age group 1926: Eclipse of the Sun 1930: Younger Maina age group (“Silobai”) circumcision) 1931: Locust invasion 1933: First Chuma age group (circumcision) 1939: Second World War referred to by the Kipsigis as “Lugetab Talian” 1948: Eclipse of the Sun 1952: Emergency/ Mau Mau 1961: Tuberet (flood) 1963: Kenya attained independence 1966: Jaramogi Odinga resigned as the Vice-President 1969: Tom Mboya assassinated 1975: J.M. Kariuki assassinated 1978: Death of Jomo Kenyatta/ Daniel Moi became president 1982: Attempted military coup 1984: Yellow maize locally called ‘spi nsi’ introduced 1988: Infamous Mlolongo election by KANU Marital Status 52. For all persons 14 years and above, ask if they are/or have ever been married. Select the appropriate respondent’s current marital status and record it in the space provided. Accept what people tell you about their marital status and do not embarrass them by asking unnecessary questions about their marriage. Please note that:
Never married include those with children but have never married Divorced means that all legal formalities have been completed and there is no chance of reunion. Separated means the couple are no longer living together and are in the process of reconciliation or divorce. “Separated” does not include persons living separately in two households for purposes of work or other convenience.
9 In census and survey work, there are hardly any guidelines on how to compute age in completed years using the date of birth (day, month and year). However, according to the Age of Majority Act, Cap 33, “in computing the age of any person the day on which he was born shall be included as a whole day and he shall be deemed not to have attained such age as may be specified until the beginning of the relevant anniversary of the day of his birth”.
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Absence/ presence 53. In column 18, indicate whether the household member listed usually resides in the holding and his/her regularity of residency using the codes given at the bottom of the questionnaire. Education 54. Under column 19 write “Yes” and code “1” if the respondent is attending school or college fulltime. Enter “No” and code “2” if the respondent is not attending school or college fulltime. 55. Under column 20 state the “highest grade attained” for each member of the household, and enter the appropriate code. This should be the highest grade completed at the end of the previous schooling year (1997). Column 21 refers to class/ form completed in that educational cycle. The completed class/ form in any type of educational institution should range between 1 and 8 years, while columns 22-23 refers to the year of completion e.g. enter “97” for year 1997. Thus for a member of the household whose highest grade in formal education was Kenya Certificate of Secondary Education/Cambridge Overseas School Certificate or London General Certificate of Education (GCE) - Ordinary Level, you should code “4” in column 20 and “4” in column 21; “4” standing for the Secondary Education code and “4” standing for the four years spent at this educational level. Reasons for not Completing the Cycle 55. If a member of the household dropped out of school before completing an education cycle, find out the reason why. In ordinary usage, someone who has completed an education cycle e.g. after doing CPE and does not continue to Form One has not dropped from school. If, however, someone stops schooling at Form Three, then he has dropped from school. However, for the purpose of this survey, those who completed the primary education cycle and did not proceed to secondary school will be counted as dropouts. The question should only be asked of those who dropped out of the education cycle during the period 1993-96. Literacy 57. For those household members not in school and are above 8 years of age, ask whether the member can read or write a simple statement in any language, and record the responses in columns 25 and 26, respectively. Vocational/ Professional Training 58. Solicit information on the training the respondent has had. Respondents may have had some of each or possibly none at all; but this column seeks particulars of non-formal or tertiary education, as opposed to formal education particulars sought in columns 20, 21, 22-23 and 24. Enter the appropriate code in column 27 for each member of the household as given at the bottom of Form B/S/L/1. Main Occupation 59. This question applies to all members of the household aged 8 years and above. Main economic activity/occupation means the dominant activity where the household member spends most of his/her time. If a member regularly works in, for example, trading/business, for over 50 percent of his/her time, then the work he/she is engaged in is the main occupation. The categories of the occupation codes for Column 28 are given at the bottom of the Form. Code 8 (“not applicable”) applies to children below 8 years.
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Migration 60. An in-migrant is a person who enters a migration-defining area by crossing its boundary from some point outside the area, but within the same country; while an out-migrant is a person who departs from a migration-defining area by crossing its boundary to a point outside it, but within the same country. An emigrant is an international migrant, departing to another country by crossing an international boundary. In a national survey, information on out-migration from a particular migration-defining area is collected from households in the destination districts. Out-migration data will not be collected in this survey. 61. Column 29 refers to the place where one born. The place of birth refers to mother’s usual residence when the index child was born. The codes are: within sub-location, within location but outside sub-location, within Bomet district but outside location, outside Bomet district, and outside the country. For those born outside Bomet district, record district of birth in columns 30-31 using the district codes given in the Appendix of this Manual. Membership in Self-help Groups 62. Ask the respondent whether there are any household members aged 15 and over who are members of community-support groups and code 1 for “Yes” and 2 for “No” in Column 32. In column 33, code the type of group to which the person belongs from the list given on the Form. Sickness 63. Indicate whether the household member has been sick in the last two weeks in column 34, type of sickness in column 35 only for those who responded “Yes” in column 34, and actions taken to restore health in columns 36 and 37. The first action is to be coded on column 36 and the second action on column 37. Responses to a sickness episode need to be interpreted within a model of sickness experience i.e. the sequence of actions people take when they fall sick. For example, the first health restoration action may not have led to health restoration, and the sick person may have “shopped” for another health restoration point. “OTC drugs” in the Form means “over-the-counter” non-prescribed drugs. Disability 64. A disability is a limitation in an individual’s ability to perform an activity in a manner that is considered to be normal. Impairment is an abnormality in the structure or function of a part of the body or mind. Disabilities are caused by impairments, which are in turn caused by diseases, injuries or congenital (inborn) or peri-natal conditions. Disabilities reported in the survey should have had duration of at least six months. Disabilities can be:
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Difficulties in seeing (visual defects)
Includes all people who have difficulty in seeing and the completely blind. The mere possession of a functional pair of squint eyes does not constitute a disability. A squint (strabismus), often called “crossed-eyes”, is a condition in which the eyes are not properly aligned with each other. One eye is either constantly or intermittently turned in (esotropia) or out (exotropia).
Difficulties in hearing
Includes all people who have difficulty in hearing and the completely deaf.
Difficulties in speaking
Includes all people who have difficulty in speaking and those who have complete loss of speech, excluding stammerers/ stutterers (with difficulties in pronouncing words beginning with certain letters such as B, D, G, K and V) e.g. those who skip letter K. Lisping is a common form of stammer and consists in the substitution of th sounds for those of s and z (Barnard, 1930; Fletcher, 1914).
Upper limbs A person with (a) one arm or both too short or too long or deformed in such a way as to prevent normal functioning; or (b) armless.
Lower limbs A person with (a) one leg or both too short or too long or deformed in such a way as to prevent normal functioning; or (b) legless.
Hunch A person with a deformity of the spine or sternum with visible protruding (heaped) muscles either on the back or the chest may be referred to as a hunch.
Mental retardation
Includes conditions which affect a person’s ability to learn, to acquire knowledge and to adapt to environment which other people of the same age and within the same environment are able to cope with.
65. Some respondents may be reluctant or shy to talk about disabled household members. Your duty is to make sure that you collect the information on disability using the best diplomacy you can bring to bear. Remind the respondents that the information will be kept confidential. If a household member has multiple disabilities, for example difficulties in seeing, upper limbs and hunch, the responses should be entered sequentially separated by a “,” as follows “1, 4, 6” in column 38. Skip Sequence 66. The skip sequences for Form B/S/L/1 are as follows: (a) If the response to column 19 is “Yes”, skip columns 24, 25, 26, 27 and 28. (b) If the response to column 29 is 1-3, skip columns 30-31. (c) If the response to column 32 is “No”, skip column 33. (d) If the response to column 34 is “No”, skip columns 35, 36 and 37. CHILD IMMUNIZATION AND BREASTFEEDING (FORM B/S/L/2) 67. This Form solicits information on child immunisation for all children in the household aged under 60 months. Children eligible for inclusion in Form B/S/L/2 are those whose recorded age in Form B/S/L/1 is 04 years since 04 completed years translates to a maximum of 59 months. Columns 9-10 record serial number of mother as given on the first form (Form B/S/L/1). Columns 11-12 record the serial number of the index child within the household as given on the first Form (Form B/S/L/1). It would be advisable to enumerate children in the order in which they are listed in Form B/S/L/1. 68. Record the names of the children in the space provided. Give at least two names. Record the month and year of birth in columns 13-14 and 15-16, respectively. For example, a child who was born in July 1995 will be recorded as 0795. This must be entered for every child, and if not known, probe and estimate. If the child has a health card, use the card as the source of information on the date of birth.
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69. Record place of delivery and the personnel who attended the mother in columns 17 and 18, respectively. A traditional birth attendant (TBA) is recognized as such by the community. Other community personnel who assisted in delivery should be recorded under “other”. A child delivered in a health centre/ dispensary is expected to have been assisted by nurse/ midwife, while those born in hospitals should be recorded as having their delivery assisted by doctors whether a doctor or nurse assisted. The respondent should also indicate the name of the hospital/ health facility to facilitate editing of the completed Form. 70. The objectives of the Kenya Expanded Programme on Immunization (KEPI) is to ensure that all children are vaccinated against measles, polio, tuberculosis, tetanus, diphtheria and pertussis, by the first birthday. Primary healthcare facilities are widespread in all the districts to ensure delivery of quality immunization services throughout the country. At the age of one, a fully-immunized child should have received BCG against tuberculosis and polio I at birth; polio II and III and DPT I, II and III (against diphtheria, pertussis and tetanus) at 6, 10 and 14 weeks, respectively; and measles at nine months. A “booster” immunization of Polio and DPT is given after 5 years. KEPI provides immunization cards for each child which gives a record of the immunizations. 71. Ask the mother if the child has a health card (any written document should be taken as a card). Code “1” for “Yes” if the card is available for your perusal and “2” for “No” in column 19. Check the vaccines administered from the health card and complete the appropriate columns 21 to 29. Check if the child has a BCG scar and record the response in column 20. If the health card is not traceable, ask the mother for details of immunization history. For those without cards, you are supposed to specify how each is given so the mother will know which vaccine we are talking about. A BCG vaccination against tuberculosis is an injection in the left forearm that makes a scar; polio vaccine is drops in the mouth; and an injection against measles is given in the top part of the right arm. It is also important to remember that a child can receive a vaccine but no record is made on the card. 72. Ask the respondent if the child is still breastfeeding. Enter 1 for Yes and 2 for No in column 30. Ask mother the length of time in months she exclusively breastfed the child without giving any other food, i.e. milk or semi-solid food to the child. If exclusively breastfed for less than one month, code ‘00’. If breastfeeding is still continuing, then the number of months breastfed is EQUAL TO THE AGE OF THE CHILD. If breastfeeding has stopped, ask the respondent how old the child was when he/she stopped breastfeeding completely. Enquire from the mother as to what type of supplement the child was first fed on and enter the response in column 35. Skip Sequence 73. The only skip sequence for Form B/S/L/2 is: If the response to column 30 is “Yes”, skip columns 33-34 on “months breastfed” since it will be identical to the age of the child. HOUSING, AMENITIES AND ASSETS: FORM B/S/L/3 The Main Residential Structure 74. Pick the main material used for the wall, floor and roof and code appropriately in columns 9, 10 and 11, respectively. Under the general heading of “Main House”, enter the number of rooms, number of windows, number of persons who usually sleep in the house, whether livestock also sleep in the house, and whether the household’s kitchen is part of the main house. If kitchen is separate from the main house, enter in the appropriate columns the number of windows, number of persons who usually sleep in the kitchen, and whether livestock also sleep in the kitchen.
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Sources of Water 75. Ask “What is the main source of water?” This is the source from which the household draws its water for most part of the year. Pick the main source of water out of the listed options and put down the corresponding code. If the main source of water is not among the sources listed in columns 21 and 22, specify it under “other” and code “8”. Some of the main sources of water include: Well: A man-made shaft dug in the ground from which water is obtained. Water is drawn
using buckets. A private well is one that is exclusively used by occupants of the dwelling unit; whereas a common well is communally used.
Borehole: Same as the well, but deeper than a well and has pump for drawing the water into a tank,
buckets, etc. A private borehole is one that is exclusively used by occupants of the dwelling unit; whereas a common borehole is communally used.
River/Stream: It is a large natural body of water flowing in its own bed. Please indicate the particular
river from the options provided. Spring: This is a place where water springs or wells up from earth or underground. Dam: A reservoir formed by building a barrier across a river to hold back water and control its
flow. A lot of these dams are built in dry areas of Kenya. Pond: A small area of still water which usually collects after rain or through an underground
drainage. Jabias/Tanks: Rainwater harnessed from any catchment into a hole/tank and used for domestic
purposes. Vendor: Refers to water purchased by households from mobile sellers or distributors. Examples
of ferrying include cart, bicycle, individuals, truck etc. The source of the water may be known or not, by the household.
76. Distance to water source one-way should be recorded in kilometres. On who is mainly responsible for water collection, “worker/ vendor” includes paid workers who are not members of the household and water sold from vendors. The amount of water collected is supposed to be the average rather than what was collected on the day prior to the interview. A household that does not purchase water from a vendor should leave columns 29-30 blank. Column 31 solicits information on method of water storage mainly used by the household, while column 32 is on whether the household does anything to the water before drinking. Toilet Facilities 77. Ask “Where do members of this household go for toilet?” Pick the relevant option and write its corresponding code under column 33. A flush is a toilet facility using water disposal system, regardless of whether it is exclusively used by the household or shared by occupants of two or more dwelling units. If the household has no toilet, probe why and record the appropriate answer in column 34. “Rocks” refer to difficulties in digging toilets due to rock formation, while “Soil” refers to lack of percolation and subsequent overflows especially during wet season. The codes given for column 34 on why the household does not own a toilet may not be meaningful in the local circumstances. You should put the explanation given by the respondent in the space provided at the bottom of the Form. Rubbish Disposal 78. Different methods of disposal of vegetable and other wastes include burning, burying, compost pit, and crude dumping.
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Main Cooking Fuel 79. Ask “What is the main cooking fuel used in this household?” Note that some households may use electricity, paraffin, gas, firewood, charcoal, all at the same time. The answer required here is the fuel used most of the time. Put down the appropriate code. Main Type of Lighting 80. Enter the appropriate code. Note that paraffin lamps include lanterns, pressure lamps and karabai (one made out of tin), etc. Distance to Social Amenities 81. Ask the respondent to give you the distance (in kilometres) from the dwelling unit to the nearest facility, and record the answers in the spaces provided. The facilities are food market, primary school, secondary school, and dispensary/ hospital. In this survey, the health facilities are hospitals, health centres, dispensaries or clinics, but exclude private practitioners unless used by the household. Assets Owned 82. In the case of assets owned by the household, please the record the number of each respective asset owned. Enter “0” in the appropriate column if the household does not own the asset. For example, if the household has two bicycles, record 2 under column 46. Only operational or serviceable assets should be recorded. An operational radio without batteries should be recorded as an asset. Skip Sequence 83. The skip sequences for Form B/S/L/3 are as follows: (a) If the response to column 17 is “No”, skip columns 18-20. (b) Only those whose responses to column 33 are 2-5 should respond to column 34. HOUSEHOLD EXPENDITURE 84. The enumerator should fill the identification particulars section. If there are two or more spenders in the household, record combined information for all spenders. i) Under each item, indicate the quantity purchased in the month of November 1997 for each of
the specified units, e.g. 10 debes of maize grain. ii) Indicate the unit of measurement of the item, e.g. kilogram, bottle, metre, bag, litre, etc.
Whenever possible all item quantities should be converted to standard units, e.g. kilograms, litre, metre, numbers, etc. If the item quantities are given in non-standard units, the enumerator, with the help of respondent, should convert them into standard units. If and only if the enumerator is unable to identify the correct code, then enter code “5” for “other” and specify the unit reported as used in the transaction of the item.
iii) Enter the price per unit and full value in Shillings, irrespective of whether it was bought in cash
or on credit.
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iv) Since Forms B/S/L/4A and B/S/L/4B solicit information on purchases, separate copies of the Forms should be completed on own consumption (withdrawals from business for household use) which will be valued as if it were bought i.e. at prevailing market prices.
85. The enumerator should make sure that the total costs per food item are actual rather than imputed. To countercheck information on prices, a retail price survey will be conducted alongside the household survey to determine the prevailing market prices which will be used to convert food costs to weight for the purpose of estimating calorie supply by the use of food-to-energy conversion tables. The retail market survey will entail purchasing the food items in representative markets in the location, and then weighing them later. HOUSEHOLD REGULAR EXPENDITURES FOR A MONTH: FORM B/S/L/4A & 4B 86. The regular expenditure categories include food items, cooking and lighting fuels, water, household operations, alcoholic beverages and tobacco, transport operating costs (e.g. fuel and repair, and use of public transportation), personal care, medical, and other items and services that are purchased regularly in a month. This excludes durable and semi-durable items. The item transactions cover purchases only, as gifts given out and consumption of own produce are picked up in other parts of the questionnaire. 87. Bread refers to all types of bread including biscuits, cakes, chapattis, mandazi, buns, scones, and so on. The cereals to be covered in the survey are maize (grain and flour), rice (grain), wheat (flour), millet (grain and flour) and sorghum (flour). Beans include all varieties excluding French beans. 88. Beef should include all forms of cattle meat i.e. beef with bones, beef without bones, bones, beef sausages and offal (matumbo). “Other meat” is likely to include meat of wild game which does not cost anything. The enumerators should indicate the animal whose meat is recorded and the weight in kilograms, but indicate that total cost is “0”. 89. Examples of cooking fats are Kimbo, Joma, Kasuku and cowboy. Cooking oils refer to liquid oils such as Elianto, corn and salad oils. “Others” refer to oils such as lard from butcheries. Expenditures on fruits include ripe bananas. The list of commonly used vegetables and roots are indicated in the questionnaire. All other types of vegetables such as pumpkins, coriander (dania), spinach, amaranthus (terere), and so on should be coded under “other vegetables”. Milk refers to any form of milk e.g. cow, goat, sheep and camel, whether packeted or unpacketed. Sugar includes white, brown and jaggery (nguru). Cocoa includes drinking chocolate and Milo. Record the value of meals eaten out in columns 57-60. 90. Note that where a household pays a porter to deliver water or purchase water from neighbours, the expenses should be added when calculating water expenses incurred by the household last month. Water expenses should only include expenses on water for domestic use. 91. Tobacco and alcoholic beverages include tobacco, khat (miraa) and cigarettes. Transport and communication expenditures include car/motor cycle service/repair, bicycle repair, petrol, diesel and engine oil expenses, and other costs e.g. bus and matatu fares. 92. Ask respondent whether the household spent any money in the last month on cooks, housemaids (ayahs), or watchmen and enter the responses in Form B/S/L/4B, columns 25-28. Any amount spent on these workers should be recorded even if the service rendered was for a shorter duration. “Other personal care” include powder, soap, toothpaste, lotions, deodorants, perfumes, aftershave, body oil, ladies toiletries, other.
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HOUSEHOLD NON-REGULAR EXPENDITURES FOR ONE YEAR: FORM B/S/L/5 93. The enumerator should probe the respondents to recall all the possible transactions of such goods and services which the household made in the last one year. This category includes clothing and footwear, education, furniture, etc. The treatment of the items should be the same as for regular expenditures only that the reference period has changed from one month to one year. 94. “Other clothing” includes blankets, bedsheets, towels, clothing materials, handkerchiefs and so on. School uniforms should be recorded under “education” expenses rather than “clothing and footwear”. Other footwear costs include repair, polish, other maintenance, and so on. 95. Other education expenses include (a) transport/ travel to school e.g. day students spend daily fares and boarders spend bus and matatu fares to boarding school; (b) feeding (day students) and boarding (boarding students) if not part of the fees; (c) individual tutoring carried out within the school compound and outside the school; and (d) compulsory school development levies. The PTA School Development Fund only includes compulsory and fixed development fund decided by Parents-Teachers Associations, whose collection is enforced in the same manner as other regular school charges. Furniture include the purchase and repair of sofas; dining, dressing, working tables; chairs, beds, stools, cupboards, bookshelves, wardrobes, etc. CROP PRODUCTION AND DISPOSAL: FORM B/S/L/6 96. Agricultural costs include: (a) Seeds (b) Transportation of inputs (c) Fertilizers (d) Sprays/ chemical application (e) Farm labour which includes all labour hired for crop-related activities. Labour can be used for
land preparation, planting/ transplanting, first weeding, top dressing, harvesting, etc. (f) Transport to market (g) Lease/ rent of land (h) Purchase of agricultural implements 97. In the local context, the peak of the long-rains is March-April and the short-rains are August-September. Therefore short-rains will refer to August-September 1996, while the long-rains will refer to March-April 1997. Consequently, the information on seasons will first be solicited on short-rains first before covering long-rains production. 98. Enter the area in acres to one decimal place under the fore-mentioned crops during the last long rains and short rain seasons separately. Area planted should include all land accessed by the household, whether owned or not. If the area under crop is 3.4 acres enter 003.4 and 034.0 if it is 34 acres. In case of inter-cropping, enter the acreage under each crop but indicate in the second row that cropping was on mixed stand. In cases of seeds, record costs. In case of maize seed, two rows are provided, one for certified and the other for uncertified. In the case of certified seed, specify whether 511, 614 variety, etc in brackets. For rows 5 to 15, enter the respective costs.
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99. Agricultural labour may either be family or hired casual and regular labour. Family labour is unpaid household labour used on the holding for agricultural purposes, excluding labour used for collecting water, firewood, child-minding, etc. Casual labour is labour employed to do agricultural work on the holding and paid either in cash or in kind on a daily basis, while regular labour is employed on the holding on a regular basis and usually paid in cash or in kind on a monthly or weekly basis. Rows 7-11 solicit information on costs of hired labour. The cost of agricultural implements should be recorded once on the maize columns since the implements are likely to be used for all crops. 100. In Form B/S/L/6B, enter the quantity in kilograms of the crop harvest for each season. Crop disposal should be broken down to sales (farm-gate, local market, cooperative, other outlets), given to labour, retained as seed, home consumption, gifts given out, and quantity in store at the time of survey. The quantity harvested may not balance with disposal due to postharvest losses e.g. theft, destruction by animals especially elephants, pests, etc. If such situations arise during the survey, you should give details in the questionnaire and the notebook provided. 101. Form B/S/L/6B also solicits information on the major factors inhibiting production (lack of market outlet, poor roads, inadequate rain, lack of inputs, high cost of inputs/labour, inadequate land, poor extension services, poor prices of output, etc). The codes for factors inhibiting crop development are given at the bottom of the Form. Probe to obtain the most serious of all problems affecting the particular farmer. If there is more than one problem, enter the codes separated with “,” starting with the most serious problem. The Form also solicits information on crop husbandry, namely, method of land preparation (burning, burning and digging/ploughing, digging/ ploughing), implements used in land preparation (tractor, plough, hand hoe, other), and method of planting (broadcasting, line planting). Broadcasting is planting or sowing seeds across an area by scattering by mechanical means or by hand. Using your hands is the most commonly used method of broadcast planting, especially in small areas. LIVESTOCK PRODUCTION AND DISPOSAL: FORM B/S/L/7 102. Livestock costs include: (a) Expenditure on livestock purchases (b) Cost of fodder (c) Cost of dipping/spraying (d) Mineral supplementation/salt (e) Concentrate feeding (dairy meal) (f) De-worming/drugs (g) Animal vaccination (g) Other veterinary services excluding vaccination (i) Livestock labour which include all labour hired for livestock-related activities (j) Lease/rent of land for livestock purposes 103. The first section of the Form solicits information on changes in livestock in the last 12 months, i.e. December 1996 to December 1997. Other poultry includes ducks, turkey, pigeons, doves, etc. Enquire the number of the different categories of livestock which was owned by the household 12 months ago, i.e. December 1996. The current stock of livestock is supposed to equal the stock one year ago and acquisitions (bought, born and gifts received) minus disposals (sales, home consumption, deaths and gifts
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given out). If a household member engages in livestock marketing as a business, the sale of livestock which is not from his/her own herd should be recorded under Form B/S/L/8 (own-account worker). Probe as accurately as possible the value of each sale of the different categories of livestock by the household in the last 12 months and record the total. 104. To be able to capture information on animal vaccines given free of charge, you should first seek information on whether the animals were vaccinated. If given free of charge, record “0” and cross it with a vertical line slanting forward. 105. List the major factors inhibiting increased livestock production in the farm (holding). These problems are listed at the bottom of the questionnaire. Probe to obtain the most serious of all problems affecting the particular farmer. If there is more than one problem, enter the codes separated with “,” starting with the most serious problem. The last section of the Form solicits information on disposal of livestock products (milk, hides, eggs, etc). Some boxes are shaded since no information is expected, and to avoid embarrassing situations e.g. the box on “number consumed by the household” with respect to “donkeys”. HOUSEHOLD NON-AGRICULTURAL INCOME: FORM B/S/L/8 106. Form B/S/L/8 has four sections: paid employee income, own-account worker, transfers and other sources of income, and land holding. PAID EMPLOYEE RECORD 107. This section seeks information on incomes of paid employees in the household. Paid employees are individuals who work for pay. The reference period is one month. Serial Number and Name 108. Begin a line for each individual. Fill in the serial number and name of the individual. Be sure the serial number of each individual is the same as that reported on Form B/S/L/1. Type of Industry 109. Try to determine the industry or economic activity in which the respondent is working. Economic activity is defined in terms of kinds of goods produced or services supplied by the unit or establishment in which the person works. Write down the main economic activity and its corresponding code. However, if you are unsure of the appropriate activity, enter any relevant information in the space provided in columns 11-12. For example, you may wish to enter the main products of the company or institution employing the household member, or the services it provides. This information is important and the survey personnel will use it to assign the correct industry or activity. The list of industries or activity codes include: agriculture, forestry, fishing, mining and quarrying, manufacturing, construction, electricity and water, wholesale/ retail trade, personal/ household services (e.g. repair of motor vehicles and personal and household goods), hotels and restaurants, transport and communications, finance and insurance services, public administration and security, education, health, and other not elsewhere classified. Monthly Cash Income 110. Monthly cash income refers to cash incomes from paid employment. Respondents may be hesitant to disclose their incomes, and you should be careful not to express any interest in their answers. Do not offer any figure to the respondent. Some respondents may wish to have their names removed from the Form before they answer this question. If they wish to use initials only, that is sufficient. However, be sure to enter the proper serial number of the respondent. Also, some respondents may wish
115
to keep this information from their spouses. One possibility is to have them write their earnings on a slip of paper and hand it to you or show you their payslips. To help you fill particulars pertaining to monthly cash incomes, it is necessary to note that in normal circumstances, “gross salary” is equal to “basic gross salary” plus “housing allowance” plus “other allowances and benefits, commissions and gratuities”. 111. Monthly deductions are essentially compulsory. They are regular deductions like income tax, NSSF, NHIF, local authority service charge, pension dues, union dues, etc. If the respondent has other deductions like loan repayment, life policy premiums, etc, these are not compulsory deductions although they might appear in his payslip, and should not be netted. Total gross income less all the above deductions will give the net income of the respondent i.e. the take-home-pay plus non-compulsory deductions e.g. voluntary savings and servicing of cooperative/ bank loans. INCOME OF BUSINESS OWNERS AND THE SELF-EMPLOYED 112. The Form seeks particulars on incomes of business owners who are essentially self-employed persons. Self-employed persons are those individuals who operate an unincorporated enterprise or business. The business may be an office, shop, factory, roadside stand, matatu, and may be located at the home (e.g. home-brewed beer and wine for sale) or have no fixed location. Serial Number and Name 113. Begin a line for each individual, and fill in the serial number and name of the individual. Be sure the serial number of each individual is the same as that reported on B/S/L/1 for that particular individual. Industry 114. For all household members 12 years and above and who are business owners or self-employed, fill in the appropriate industry or activity code as described in the paid employee record. If a household member operates businesses in more than one activity or operates a business which encompasses more than one activity, for each activity repeat the serial number of the household member and fill the details of the activity on a separate line. However, if you are unsure of the appropriate activity, enter any relevant information in the space provided in columns 25-26. Status 115. The respondent may be either owner of the enterprise he operates or an unpaid family worker. An unpaid family worker is usually a person who works without pay in an economic enterprise operated by a related person living in the same household. Thus, the person who works in his/her own enterprise and the unpaid family worker are both self-employed persons. Write the appropriate status and enter the corresponding code in column 27. For respondents who are owners of business, record incomes in columns 28-32 and 33-37. Unpaid family workers should not answer questions relating to income from the enterprise. Monthly Gross Income 116. Gross entrepreneurial income consists of profits i.e. operating surplus before allowance for depreciation. If more than one member of the household are engaged in a particular family enterprise, all the profit should be recorded against the household head. Write down the total amount received from all sales of goods and services after deductions of wages, rent, cost of goods, etc. If certain goods and services are not physically sold but removed for household use, impute a value which would have been received if the goods were actually sold and enter this amount as in-kind income. For instance, retail-shop owners may take household goods for home use e.g. sugar or maize flour. The net profit made by the business is the net income. A minus sign should precede a negative net income (loss), while a positive sign
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must precede a profit. If the business is co-owned give the respondent’s share of net income from the business. HOUSEHOLD TRANSFERS 117. The Form seeks particulars on all cash and in-kind transfers into and out of the household during the month. Transfers are non-refundable receipts or payments which would be in the form of gifts or grants. One should also look at transfers as receipts or payments for services not rendered. Gifts received or given out should exclude livestock since the information was collected on Form B/S/L/7. Details of food relief should include item name, date (MM) received, quantity and value. The enumerator should differentiate maize grain (for consumption) from maize seed for planting, and record the responses on separate rows even if they were given in the same month. ALTERNATE SOURCES OF INCOME 118. These include income from investment (interest/dividends), rental income, and lease of land, and the reference period is one year. Rental income is for letting out property he/she owns, excluding land which will be recorded separately. You should exclude very temporary dwellings e.g. those built of cartons. Interest income includes earnings from bank savings, and investments in stocks and bonds. LAND HOLDING 119. Solicit information on all land parcels owned by the household and record “Yes” or “No” in column 87 and the location of each parcel in column 88. Space is provided for three parcels. If the household owns more than three parcels, record the details at the bottom of the Form. The codes for location of land are the same as those in Form B/S/L/1, column 29 except code 5 (outside Kenya) which is out-of-scope. Enquire the size (in acres) of the holding to the nearest one decimal place. If the holding size is 3.4 acres enter 003.4. Enquire also whether the holding has a title deed, and enter 1 for Yes and 2 for No. For a household that does not own land, enquire how it obtains access to land for crop and/or livestock purpose, and the size of land the household accesses and record accordingly. Land purchased should be included under land owned whether issuance of title deed has been completed or not. However, land expected to be acquired from parents under inheritance should be recorded as free access from parents rather than owned. Skip Sequence 120. If the response to column 87 is “No”, skip columns 88, 89-92 and 93.
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PROCEDURE FOR ANALYZING INCOME AND EXPENDITURE DATA
121. Household Income
1.1 Income from rural farm (crops and livestock)
1.2 Income from paid employment
1.3 Income from self-employment (working alone) and employer (business) enterprise 1.2.1 Cash income 1.2.2 In-kind income (domestic consumption of goods and services) 1.2.3 Net income (1.2.1 + 1.2.2)
1.4 Income from rents, interest, pensions, etc 1.4.1 Lease/rent of land and other rental income 1.4.2 Interest/dividends received 1.4.3 Pensions
1.5 Cash transfers (remittances)
1.5.1 Cash transfers in 1.5.2 Cash transfers out 1.5.3 Net cash transfers (1.5.1 less 1.5.2) 1.5.4 In-kind transfers in 1.5.5 In-kind transfers out 1.5.6 Net in-kind transfers (1.5.4 less 1.5.5) 1.5.7 Food relief
122. Household Consumption Expenditure
1.1 Food: Purchases and own consumption 1.2 Fuel and power 1.3 Water 1.4 Household operations (soaps and detergents, batteries, matches, domestic workers) 1.5 Alcoholic beverages and tobacco 1.6 Transport and communications 1.7 Personal and medical care 1.8 Clothing and footwear 1.9 Education 1.10 Furniture, furnishings, household equipment and operation 1.11 Miscellaneous goods and services
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DISTRICT CODES
11 Nairobi 21 Kiambu 22 Kirinyaga 23 Murang’a 24 Nyandarua 25 Nyeri 31 Kilifi 32 Kwale 33 Lamu 34 Mombasa 35 Taita-Taveta 36 Tana River 41 Embu 42 Isiolo 43 Kitui 44 Machakos 45 Marsabit 46 Meru 47 Makueni* 48 Tharaka-Nithi* 51 Garissa 52 Mandera 53 Wajir 61 Kisii 62 Kisumu 63 Siaya 64 Homa Bay* 65 Migori* 66 Nyamira* 71 Kajiado 72 Kericho 73 Laikipia 74 Nakuru 75 Narok 76 Trans Nzoia 77 Uasin Gishu 78 Bomet* 81 Baringo 82 Elgeyo Marakwet 83 Nandi 84 Samburu 85 Turkana 86 West Pokot 91 Bungoma 92 Busia
119
93 Kakamega 94 Vihiga* * Newly created districts.
120
SURVEY QUESTIONNAIRES
121
ACTIONAID-KENYA
BOMET RURAL DEVELOPMENT INITIATIVE BASELINE SURVEY, DECEMBER 1997
HOUSEHOLD COMPOSITION FORM B/S/L/1
Enumerator________________ Supervisor_________________ Date of interview (dd/mm/yyyy) ___________ Location Sub-location Village Household RT Replacement 1=Yes, 2= No Final Interview Status (see Manual) 1 2 3|4 5|7 8 9 10 Name Code 1
TO BE COMPLETED FOR ALL MEMBERS OF THE HOUSEHOLD Serial No.
Name of household member
Relation to head
Sex Age in completed
years
Marital Status
Absent/ Present
At School/ college fulltime
Highest level
reached
Class/ Form in
education cycle
Year highest class/ form
completed
Reason for not
completing education
cycle
If NO in column 19 Highest vocational/ professional certificate attained
Main occupation
Where was
…born?
If born outside Bomet, District
code
Is…Member of any self-help group?
If yes in
Col. 32, type of
group
Sick last two
weeks?
If yes in column 34 Does …have
difficulties in
See code
1 =M
2 =F
See code
See code
1 = Yes2 = No
See code
See manual
See code Can read a simple
statement in any
language? 1 = Yes 2 = No
Can write a simple
statement in any
language? 1 = Yes 2 = No
See code See code See code
See manual
1 = Yes 2 = No
See code
1 = Yes 2 = No
Type of sickness
(see code)
First action taken (see
code)
Second action taken (see
code)
See code
11|12 13 14 15|16 17 18 19 20 21 22|23 24 25 26 27 28 29 30|31 32 33 34 35 36 37 38 1 2 Column 13: 1 = Head, 2 = Spouse, 3 = Son, 4 = Daughter, 5 = Parent, 6= Other relative, 7= Non-relative Column 17: 1=Never married, 2=Married monogamous, 3=Married polygamous, 4=Separated, 5=Divorced, 6=Widowed, 7=Other (specify) Column 18: 1=Usually present, 2=Usually absent less than a month, 3= Longer absence Column 20: 1=None, 2=Pre-primary, 3=Primary, 4=Secondary, 5=University, 6=Other (specify) Column 24: 1=Pregnancy, 2=Marriage, 3=Lack of fees, 4=Failed exam, 5=Illness, 6=Employment, 7=Family labor, 8=Not interested, 9=N/A Column 27: 1=None, 2=Trade tests 1-3, 3=Teaching, 4=Medical, 5=Other postsecondary Column 28: 1=Unpaid family worker, 2=Crop/ livestock farmer, 3=Public sector employee, 4=Private sector employee, 5=Own account worker (owner), 6=Student, 7=Unemployed, 8=N/A, 9=Other (specify) Column 29: 1=Within sub-location, 2=Within location/ but outside sub-location, 3=Within district/ but outside location, 4=Outside Bomet district, 5=Outside country Column 33: 1= Merry-go-round (cash), 2=Help with labor, 3=Livestock production/ marketing, 4=Beekeeping, 5=Posho mill, 6=Duka (shop), 7=Other (specify) Column 35: 1=Vomit/ diarrhea, 2=Malaria/fever, 3=Cough/ cold, 4=Injury/ burns, 5=Measles, 6=Eye infection, 7=Skin rash, 8=Other (specify), 9=N/A Columns 36 & 37: 1=Nothing, 2=Prayers, 3=Traditional medicine/ healer, 4=OTC drugs, 5=Health facility, 6=N/A Column 38: 1=Seeing, 2=Hearing, 3=Speaking, 4=Upper limbs, 5=Lower limbs, 6=Hunch, 7=Mental, 8=None
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ACTIONAID-KENYA
BOMET RURAL DEVELOPMENT INITIATIVE BASELINE SURVEY, DECEMBER 1997
CHILD IMMUNIZATION AND BREASTFEEDING FORM B/S/L/2
Enumerator________________ Supervisor_________________ Date of interview (dd/mm/yyyy) ___________
Location Sub-location Village Household RT 1 2 3|4 5|7 8 Name Code 2
Serial number of
mother from B/S/L/1)
Serial number of child from
B/S/L/1)
Name of child
Month/ year of birth
Place of delivery
Who delivered the child?
Does child have a
health card?
BCG scar
Has the child received each of the following vaccinations? Is child still breastfeeding?
Months exclusively breastfed
Months breastfed
Main type of first
supplement MM/YY See code See code 1=Yes
2=No 1=Yes 2=No
BCG POLIO-B (given at
birth)
POLIO 1
POLIO 2
POLIO 3
DPT 1
DPT 2
DPT 3
Measles See code
1=Yes 2=No
1=Yes 2=No
1=Yes 2=No
1=Yes 2=No
1=Yes 2=No
1=Yes 2=No
1=Yes 2=No
1=Yes 2=No
1=Yes 2=No
1=Yes 2=N
9|10 11|12 13|16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31|32 33|34 35 Column 17: 1=Hospital/ health facility, 2=At home, 3=Other (specify) Column 18: 1=Doctor, 2=Nurse/ midwife, 3=TBA, 4=Self, 5=Other (specify) Column 35: 1 = Milk other than breast, 2 = Commercial Infant Food/ Formula, 3 = Porridge: Maize/ Millet/ Other, 4 = Semi-solids, 5 = Tea, 6 = Other (specify)
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ACTIONAID-KENYA BOMET RURAL DEVELOPMENT INITIATIVE
BASELINE SURVEY, DECEMBER 1997 HOUSING, AMENITIES AND ASSETS
FORM B/S/L/3
Enumerator________________ Supervisor_________________ Date of interview (dd/mm/yyyy) ___________
Location Sub-location Village Household RT 1 2 3|4 5|7 8 Name Code 3
MAIN HOUSE Kitchen: If yes in column 17 Type of wall Type of floor Type of roof Number of rooms Number of windows Number of persons sleeping in Does livestock sleep in? Is kitchen separate? Number of windows Number of persons sleeping in Does livestock sleep in?
See code See code See code 1=Yes 2=No
1=Yes 2=No
1=Yes 2=No
9 10 11 12 13 14|15 16 17 18 19 20
Main source of water Distance to water source one way (km)
Who collects the water?
Number of 20-litre containers collected per day
Water cost - Shs of 20-litre container
Method of water storage
Water treatment before drinking
Disposal of human excreta
If no toilet, Why?
Disposal of rubbish
Wet season
Dry season
Wet season Dry season
See code See code See code See code See code See code See code See code 21 22 23|24 25|26 27 28 29|30 31 32 33 34 35
Main type of Cooking Fuel Main type of lighting Fuel Distance to the nearest (in km): NUMBER OF ASSETS OWNED
Food Market Primary school Secondary school Dispensary/ Hospital Bicycles Motorcycles Cars Radios Ploughs Tractors See code See code
36 37 38|39 40|41 42|43 44|45 46 47 48 49 50 51 Columns 9 & 10: 1=Mud/ earth, 2=Timber, 3=Stone, 4=Cement/ Bricks, 5=Other (specify) Column 11: 1=Grass, 2=Iron sheets, 3=Tin, 4=Tiles, 5=Other (specify) Columns 21 and 22: 1=Shallow well, 2=Roof catchment, 3=Pond/ dam, 4=Unprotected spring, 5=Amalo river, 6=Lelaitich, 7=Cheptare river, 8=Other (specify) Column 27: 1=Wife, 2=Husband, 3=Female children, 4=Male children, 5=Wife and female children, 6=Husband and male children, 7=Worker/ vendor, 8=Other (specify) Column 31: 1=Plastic buckets, 2=Earthenware pots, 3=Metal drums, 4= Sufurias, 5=Jerricans, 6=Storage tank, 7=Other (specify) Column 32: 1=Nothing, 2=Boil, 3=Filter, 4=Other (specify) Column 33: 1=Own pit latrine, 2=Neighbor’s pit latrine, 3=Bush, 4=Flush, 5=Other (specify) Column 34: 1=Rocks, 2=Soil, 3=Unnecessary, 4=Other (specify) Column 35: 1=Burning, 2=Burying, 3=Compost pit, 4=Crude dumping, 5=Other (specify) Column 36: 1=Firewood, 2=Charcoal, 3=Cow dung, 4=Paraffin, 5=Gas, 6=Other (specify) Column 37: 1=Firewood, 2=Charcoal, 3=Paraffin, 4=Gas, 5=Other (specify) NOTES ON COLUMN 34: ______________________________________________________________________________________________________________________________________________________
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ACTIONAID-KENYA BOMET RURAL DEVELOPMENT INITIATIVE
BASELINE SURVEY, DECEMBER 1997 HOUSEHOLD REGULAR PURCHASES FOR ONE MONTH: NOVEMBER 1997
FORM B/S/L/4A
Enumerator________________ Supervisor_________________ Date of interview (dd/mm/yyyy) ___________
Location Sub-location Village Household RT 1 2 3|4 5|7 8 Name Code 4
BREAD CEREALS BEANS MEAT Line Item MAIZE Rice Wheat Millet Sorghum Other grains/ flours Beef Goat Sheep Chicken Other meat Grain Flour Grain Flour Grain Flour Flour 9 10|13 14|17 18|21 22|25 26|29 30|33 34|37 38|41 42|45 46|49 50|53 54|57 58|61 62|65 66|69 QUANTITY 1 UNIT 2 PRICE/UNIT 3 TOTAL COST 4 FISH EGGS OILS & FATS FRUITS VEGETABLES Line Item Cooking Fat Cooking oils Butter/ margarine Other oils &fats Cabbages Sukuma wiki (kale) Onions Tomatoes Carrots Other vegetables 9 10|13 14|17 18|21 22|25 26|29 30|33 34|37 38|41 42|45 46|49 50|53 54|57 58|61 QUANTITY 5 UNIT 6 PRICE/UNIT 7 TOTAL COST 8 ROOTS & TUBERS MILK SUGAR Salt Soda and juices TEA / COFFEE AND COCOA Meals eaten out Other foodstuffs Line Item English potatoes Sweet potatoes Cassava Other roots/ tubers Unpacketed Packeted White/ Brown Coffee Cocoa and products Tea leaves 9 10|13 14|17 18|21 22|25 26|29 30|33 34|37 38|41 42|45 46|49 50|53 54|57 58|61 62|65 QUANTITY 9 UNIT 10 PRICE/UNIT 11 TOTAL COST 12 UNIT CODE: 1= Kilograms, 2 = Grams, 3 = Litres, 4 =Number, 5 = Other (specify)
125
ACTIONAID-KENYA
BOMET RURAL DEVELOPMENT INITIATIVE BASELINE SURVEY, DECEMBER 1997
HOUSEHOLD REGULAR PURCHASES FOR ONE MONTH: NOVEMBER 1997 FORM B/S/L/4B
Enumerator________________ Supervisor_________________ Date of interview (dd/mm/yyyy) ___________
Location Sub-location Village Household RT 1 2 3|4 5|7 8 Name Code 4
FUEL FOR COOKING AND LIGHTING WATER Soap and Detergents Batteries ALCOHOLIC BEVERAGES AND TOBACCO Line Item Firewood Charcoal Paraffin Gas Electricity Beer Local Brew Other alcoholic beverages Cigarettes Snuff and other tobacco products 9 10|13 14|17 18|21 22|25 26|29 30|33 34|37 38|41 42|45 46|49 50|53 54|57 58|61 QUANTITY 1 UNIT 2 PRICE/UNIT 3 TOTAL COST 4 TRANSPORT Domestic
workers PERSONAL CARE MEDICAL Other regular purchases
(specify) Line
Item Car/ motorcycle service/
repair Bicycle repair
Petrol, diesel and engine oil, etc
Other transport (buses, etc)
Haircut (men)
Hairdressing (women)
Other personal care
Hospital charges
Medicine/ injections
Other medical fees/ costs
9 10|13 14|17 18|21 22|25 26|29 30|33 34|37 38|41 42|45 46|49 50|53 54|57 QUANTITY 5 UNIT 6 PRICE/UNIT 7 TOTAL COST
8
UNIT CODE: 1= Kilograms, 2 = Grams, 3 = Litres, 4 = Number, 5 =Other (specify)
126
ACTIONAID-KENYA BOMET RURAL DEVELOPMENT INITIATIVE
BASELINE SURVEY, DECEMBER 1997 HOUSEHOLD NON-REGULAR PURCHASES FOR ONE YEAR: 1997
FORM B/S/L/5
Enumerator________________ Supervisor_________________ Date of interview (dd/mm/yyyy) ___________
Location Sub-location Village Household RT 1 2 3|4 5|7 8 Name Code 5
CLOTHING & FOOTWEAR EDUCATION Furniture Other goods and services
(specify) Line
Item Men’s
Clothing Women’s Clothing
Children’s Clothing
Other Clothing
Men’s Footwear
Women’s Footwear
Children’s Footwear
Other Footwear
School Fees
School Uniform
Books/ Stationery
Other educational costs
9 10|13 14|17 18|21 22|25 26|29 30|33 34|37 38|41 42|46 47|51 52|56 57|61 62|66 67|71 QUANTITY 1 UNIT 2 PRICE/UNIT 3 TOTAL COST
4
127
ACTIONAID-KENYA
BOMET RURAL DEVELOPMENT INITIATIVE BASELINE SURVEY, DECEMBER 1997 CROP PRODUCTION AND DISPOSAL
FORM B/S/L/6A
Enumerator________________ Supervisor_________________ Date of interview (dd/mm/yyyy) ___________
Location Sub-location Village Household RT 1 2 3|4 5|7 8 Name Code 6
Line Item Maize Finger Millet Sorghum Beans Sweet Potatoes
Short Rains Long Rains Short Rains Long Rains Short Rains Long Rains Short Rains Long Rains Short Rains Long Rains 9 10|14 15|19 20|24 25|29 30|34 35|39 40|44 45|49 50|54 55|59 1 Area planted (acres) 2 Style of Cropping (see code) 3 Certified seeds Purchased (Shs) 4 Uncertified seeds Purchased (Shs) 5 Fertilizer (Shs) 6 Agro-chemicals (sprays, insecticides etc Shs) HIRED LABOR for (Shs): 7 Land preparation 8 Planting 9 First weeding 10 Second weeding 11 Harvesting OTHER COSTS
12 Transport to market (Shs) 13 Lease/rent of land (Shs) 14 Purchase of agricultural implements (Shs)
15 Total costs Row 2:: 1=Single stand/ mono-crop, 2=Mixed stand
128
ACTIONAID-KENYA
BOMET RURAL DEVELOPMENT INITIATIVE BASELINE SURVEY, DECEMBER 1997
CROP PRODUCTION AND DISPOSAL (continued) FORM B/S/L/6B
Enumerator________________ Supervisor_________________ Date of interview (dd/mm/yyyy) ___________
Location Sub-location Village Household RT 1 2 3|4 5|7 8 Name Code 6
Maize Finger Millet Sorghum Beans Sweet potatoes Short Rains Long Rains Short Rains Long Rains Short Rains Long Rains Short Rains Long Rains Short Rains Long Rains
Line Item 9 10|14 15|19 20|24 25|29 30|34 35|39 40|44 45|49 50|54 55|59 1 Quantity harvested (kgs) 2 Value of sales: Farm-gate or road-side (Shs) 3 Value of sales: Local Market (Shs) 4 Value of sales: Cooperative (Shs) 5 Value of sales: Other outlets (Shs) 6 Average price per unit (Shs) 7 Quantity given to labor (kgs) 8 Quantity retained as seeds (kgs) 9 Quantity for home consumption (kgs) 10 Quantity given out as gifts (kgs) 11 Quantity in store now 12 Factors inhibiting production (see code) MAIN RESPONSIBILITY FOR
13 Land preparation 14 Planting 15 Weeding 16 Harvesting
17 Method of land preparation 18 Implements for land preparation 19 Method of planting
Codes for row 12: 1=Lack of market outlet, 2=Poor roads, 3=Inadequate rain, 4=Lack of inputs, 5=High cost of inputs/ labor, 6=Inadequate land, 7=Poor extension services, 8=Poor prices of output, 9=Other (specify) Codes for Rows 13-16: 1=Wife, 2=Husband, 3= Male children, 4= Female children, 5=Wife and female children, 6=Husband and male children, 7=Paid labor, 8=Other (specify) Codes for Row 17: 1=Burning, 2=Burning and digging/ ploughing, 3=Digging/ ploughing, 4=Other (specify) Codes for Row 18: 1= Tractor, 2=Plough, 3=Hand hoe, 4=Other (specify) Codes for Row 19: 1=Broadcasting, 2=Line planting, 3=Other (specify)
129
ACTIONAID-KENYA BOMET RURAL DEVELOPMENT INITIATIVE
BASELINE SURVEY, DECEMBER 1997 LIVESTOCK PRODUCTION AND DISPOSAL: DECEMBER 1996-DECEMBER 1997
FORM B/S/L/7 Enumerator________________ Supervisor_________________ Date of interview (dd/mm/yyyy) ___________
Location Sub-location Village Household RT 1 2 3|4 5|7 8 Name Code 7
Grade Cattle Zebu Cattle Goats Sheep Chicken Other Poultry Donkeys Honey
Line Item 9 10|14 15|19 20|24 25|29 30|34 35|39 40|44 45|49 1 Number in December 1996 2 Number bought 3 Number born 4 Gifts received including dowry 5 Number sold 6 Number consumed by the household 7 Number dead 8 Gifts Given out including dowry 9 Number in December 1997 10 Price per unit today 11 Income from sales (Shs) 12 Problems inhibiting production LIVESTOCK COSTS/INCOME
13 Cost of fodder 14 Dipping/spraying 15 Mineral supplementation/salt 16 Commercial feeds 17 Vaccination 18 Deworming/drugs 19 Artificial Insemination/ other veterinary services 20 Hired labor 21 Lease/rent of land for livestock 22 Other costs 23 Total costs
24 Milk production (litres) 25 Milk consumption (litres) 26 Milk sales (Shs) 27 Sale of hides (Kgs) 28 Egg production (Number) 29 Egg consumption (Number) 30 Egg sales (Number) 31 Price per egg today (Shs)
Codes for row 12: 1=Lack of market outlet, 2=Poor roads, 3=Drought, 4=Poor extension services, 5=High cost of drugs, 6= Other (specify)
130
ACTIONAID-KENYA
BOMET RURAL DEVELOPMENT INITIATIVE BASELINE SURVEY, DECEMBER 1997
HOUSEHOLD NON-AGRICULTURAL INCOME FORM B/S/L/8
Enumerator________________ Supervisor_________________ Date of interview (dd/mm/yyyy) ___________
Location Sub-location Village Household RT 1 2 3|4 5|7 8 Name Code 8
PAID EMPLOYEE INCOME SELF-EMPLOYED/ UNPAID FAMILY WORKER Name of Household member Serial No. from B/S/L/1 Industry/ activity (see code) Monthly wage Monthly pension Name of Household member Serial No. from B/S/L/1 Industry/ activity (see code) Status (see code) Monthly Income
Cash Kind 9|10 11|12 13|17 18|22 23|24 25|26 27 28|32 33|37
TRANSFERS & OTHER SOURCES (ANNUAL): 1997 FOOD RELIEF: 1997 Lease/ rent of land (receipts) Rental Income Transfers/ gifts received Transfers/ gifts given Out Interest/ Dividends Other (specify) Item name Date (mm) Quantity (kgs) Value
Cash Kind Cash Kind 38|42 43|47 48|52 53|57 58|62 63|67 68|72 73|77 78 79|80 81|82 83|86
LAND TENURE Do you own land? Where is the parcel located? Size in Acres Do you have a title deed? If don’t own, how do you access land? Acres accessed and not owned 1=Yes 2= No
1=Yes 2= No
87 88 89|92 93 94 95|98 This parcel Other parcel 1 Other parcel 2 Columns 11-12 & 25-26: 1=Agriculture, 2=Forestry, 3=Fishing, 4=Mining and quarrying, 5=Manufacturing, 6=Construction, 7=Electricity/ water, 8=Wholesale/ retail trade and personal/ household services, 9=Hotels and restaurants, 10=Transport and communications, 11=Finance, insurance services, 12= Public administration and security, 13=Education, 14=Health, 15=Other (specify) Column 27: 1=Owner, 2=Unpaid Family Worker Column 94: 1=Free/ parent, 2=Free/ non-parent, 3=Lease/ rent, 4=Squatting, 5=Landless, no access, 6=Other (specify)
